{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# pandas 进阶修炼 ｜早起Python\n",
    "<br>\n",
    "\n",
    "**本习题由公众号【早起Python & 可视化图鉴】 原创，转载及其他形式合作请与我们联系（微信号`sshs321`)，未经授权严禁搬运及二次创作，侵权必究！**\n",
    "\n",
    "\n",
    "\n",
    "本习题基于 `pandas` 版本 `1.1.3`，所有内容应当在 `Jupyter Notebook` 中执行以获得最佳效果。\n",
    "\n",
    "不同版本之间写法可能会有少许不同，如若碰到此情况，你应该学会如何自行检索解决。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3 - 数据预览与预处理\n",
    "<br>\n",
    "\n",
    "在拿到数据第一步当然是对数据做一个大概的浏览，以及对缺失值重复值进行相关处理。\n",
    "\n",
    "本小节就将练习这部分的基本操作。\n",
    "\n",
    "注意1：为了尽可能多的介绍不同方法，因此本节部分操作不是必须的。\n",
    "\n",
    "注意2:当进入到 pandas 操作数据时，很多答案并非唯一也并非最优。\n",
    " "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 初始化\n",
    "\n",
    "<br>\n",
    "\n",
    "该 `Notebook` 版本为**纯习题版**\n",
    "\n",
    "如果需要答案或者提示，可以微信搜索公众号「早起Python」获取！"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 加载数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "df = pd.read_excel(\"TOP250.xlsx\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 数据查看"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 262 entries, 0 to 261\n",
      "Data columns (total 11 columns):\n",
      " #   Column  Non-Null Count  Dtype  \n",
      "---  ------  --------------  -----  \n",
      " 0   片名      262 non-null    object \n",
      " 1   上映年份    262 non-null    int64  \n",
      " 2   评分      257 non-null    float64\n",
      " 3   评价人数    259 non-null    float64\n",
      " 4   导演      262 non-null    object \n",
      " 5   编剧      262 non-null    object \n",
      " 6   主演      262 non-null    object \n",
      " 7   类型      262 non-null    object \n",
      " 8   国家/地区   256 non-null    object \n",
      " 9   语言      256 non-null    object \n",
      " 10  时长(分钟)  256 non-null    float64\n",
      "dtypes: float64(3), int64(1), object(7)\n",
      "memory usage: 22.6+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1 - 查看数据维度\n",
    "\n",
    "先看看数据多少行，多少列，对接下来的处理量心里有个数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#df.shape\n",
    "len(df.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "262"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2 - 随机查看5条数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>片名</th>\n",
       "      <th>上映年份</th>\n",
       "      <th>评分</th>\n",
       "      <th>评价人数</th>\n",
       "      <th>导演</th>\n",
       "      <th>编剧</th>\n",
       "      <th>主演</th>\n",
       "      <th>类型</th>\n",
       "      <th>国家/地区</th>\n",
       "      <th>语言</th>\n",
       "      <th>时长(分钟)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>哪吒闹海</td>\n",
       "      <td>1979</td>\n",
       "      <td>9.1</td>\n",
       "      <td>202556.0</td>\n",
       "      <td>严定宪 / 王树忱 / 徐景达</td>\n",
       "      <td>王树忱</td>\n",
       "      <td>梁正晖 / 邱岳峰 / 毕克 / 富润生 / 尚华 / 于鼎</td>\n",
       "      <td>动画 / 奇幻 / 冒险</td>\n",
       "      <td>中国</td>\n",
       "      <td>汉语普通话</td>\n",
       "      <td>65.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>功夫</td>\n",
       "      <td>2004</td>\n",
       "      <td>8.7</td>\n",
       "      <td>816184.0</td>\n",
       "      <td>周星驰</td>\n",
       "      <td>曾瑾昌 / 陈文强 / 周星驰 / 霍昕</td>\n",
       "      <td>周星驰 / 元秋 / 元华 / 黄圣依 / 梁小龙 / 陈国坤 / 田启文 / 林子聪 / ...</td>\n",
       "      <td>喜剧 / 动作 / 犯罪 / 奇幻</td>\n",
       "      <td>中国</td>\n",
       "      <td>粤语</td>\n",
       "      <td>100.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>记忆碎片</td>\n",
       "      <td>2000</td>\n",
       "      <td>8.6</td>\n",
       "      <td>499479.0</td>\n",
       "      <td>克里斯托弗·诺兰</td>\n",
       "      <td>克里斯托弗·诺兰 / 乔纳森·诺兰</td>\n",
       "      <td>盖·皮尔斯 / 凯瑞-安·莫斯 / 乔·潘托里亚诺 / 小马克·布恩 / 拉什·费加 / 乔...</td>\n",
       "      <td>剧情 / 悬疑 / 惊悚 / 犯罪</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>113.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>辛德勒的名单</td>\n",
       "      <td>1993</td>\n",
       "      <td>9.5</td>\n",
       "      <td>890468.0</td>\n",
       "      <td>史蒂文·斯皮尔伯格</td>\n",
       "      <td>托马斯·肯尼利 / 斯蒂文·泽里安</td>\n",
       "      <td>连姆·尼森 / 本·金斯利 / 拉尔夫·费因斯 / 卡罗琳·古多尔 / 乔纳森·萨加尔 / ...</td>\n",
       "      <td>剧情 / 历史 / 战争</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>195.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>勇敢的心</td>\n",
       "      <td>1995</td>\n",
       "      <td>8.9</td>\n",
       "      <td>484179.0</td>\n",
       "      <td>梅尔·吉布森</td>\n",
       "      <td>兰道尔·华莱士</td>\n",
       "      <td>梅尔·吉布森 / 苏菲·玛索 / 布莱恩·考克斯 / 詹姆斯·科兹莫 / 辛·劳洛 / 凯瑟...</td>\n",
       "      <td>剧情 / 动作 / 传记 / 历史 / 战争</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>178.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         片名  上映年份   评分      评价人数               导演                    编剧  \\\n",
       "157    哪吒闹海  1979  9.1  202556.0  严定宪 / 王树忱 / 徐景达                   王树忱   \n",
       "120      功夫  2004  8.7  816184.0              周星驰  曾瑾昌 / 陈文强 / 周星驰 / 霍昕   \n",
       "182    记忆碎片  2000  8.6  499479.0         克里斯托弗·诺兰     克里斯托弗·诺兰 / 乔纳森·诺兰   \n",
       "7    辛德勒的名单  1993  9.5  890468.0        史蒂文·斯皮尔伯格     托马斯·肯尼利 / 斯蒂文·泽里安   \n",
       "95     勇敢的心  1995  8.9  484179.0           梅尔·吉布森               兰道尔·华莱士   \n",
       "\n",
       "                                                    主演  \\\n",
       "157                     梁正晖 / 邱岳峰 / 毕克 / 富润生 / 尚华 / 于鼎   \n",
       "120  周星驰 / 元秋 / 元华 / 黄圣依 / 梁小龙 / 陈国坤 / 田启文 / 林子聪 / ...   \n",
       "182  盖·皮尔斯 / 凯瑞-安·莫斯 / 乔·潘托里亚诺 / 小马克·布恩 / 拉什·费加 / 乔...   \n",
       "7    连姆·尼森 / 本·金斯利 / 拉尔夫·费因斯 / 卡罗琳·古多尔 / 乔纳森·萨加尔 / ...   \n",
       "95   梅尔·吉布森 / 苏菲·玛索 / 布莱恩·考克斯 / 詹姆斯·科兹莫 / 辛·劳洛 / 凯瑟...   \n",
       "\n",
       "                         类型 国家/地区     语言  时长(分钟)  \n",
       "157            动画 / 奇幻 / 冒险    中国  汉语普通话    65.0  \n",
       "120       喜剧 / 动作 / 犯罪 / 奇幻    中国    粤语    100.0  \n",
       "182       剧情 / 悬疑 / 惊悚 / 犯罪    美国     英语   113.0  \n",
       "7              剧情 / 历史 / 战争    美国    英语    195.0  \n",
       "95   剧情 / 动作 / 传记 / 历史 / 战争    美国    英语    178.0  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sample(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3 - 查看数据前后5行"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>片名</th>\n",
       "      <th>上映年份</th>\n",
       "      <th>评分</th>\n",
       "      <th>评价人数</th>\n",
       "      <th>导演</th>\n",
       "      <th>编剧</th>\n",
       "      <th>主演</th>\n",
       "      <th>类型</th>\n",
       "      <th>国家/地区</th>\n",
       "      <th>语言</th>\n",
       "      <th>时长(分钟)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>肖申克的救赎</td>\n",
       "      <td>1994</td>\n",
       "      <td>9.7</td>\n",
       "      <td>2317937.0</td>\n",
       "      <td>弗兰克·德拉邦特</td>\n",
       "      <td>弗兰克·德拉邦特 / 斯蒂芬·金</td>\n",
       "      <td>蒂姆·罗宾斯 / 摩根·弗里曼 / 鲍勃·冈顿 / 威廉姆·赛德勒 / 克兰西·布朗 / 吉...</td>\n",
       "      <td>剧情 / 犯罪</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>142.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>霸王别姬</td>\n",
       "      <td>1993</td>\n",
       "      <td>9.6</td>\n",
       "      <td>1720638.0</td>\n",
       "      <td>陈凯歌</td>\n",
       "      <td>芦苇 / 李碧华</td>\n",
       "      <td>张国荣 / 张丰毅 / 巩俐 / 葛优 / 英达 / 蒋雯丽 / 吴大维 / 吕齐 / 雷汉...</td>\n",
       "      <td>剧情 / 爱情 / 同性</td>\n",
       "      <td>中国</td>\n",
       "      <td>汉语普通话</td>\n",
       "      <td>171.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>阿甘正传</td>\n",
       "      <td>1994</td>\n",
       "      <td>9.5</td>\n",
       "      <td>1743966.0</td>\n",
       "      <td>罗伯特·泽米吉斯</td>\n",
       "      <td>艾瑞克·罗斯 / 温斯顿·格鲁姆</td>\n",
       "      <td>汤姆·汉克斯 / 罗宾·怀特 / 加里·西尼斯 / 麦凯尔泰·威廉逊 / 莎莉·菲尔德 / ...</td>\n",
       "      <td>剧情 / 爱情</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>142.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>这个杀手不太冷</td>\n",
       "      <td>1994</td>\n",
       "      <td>9.4</td>\n",
       "      <td>1922740.0</td>\n",
       "      <td>吕克·贝松</td>\n",
       "      <td>吕克·贝松</td>\n",
       "      <td>让·雷诺 / 娜塔莉·波特曼 / 加里·奥德曼 / 丹尼·爱罗 / 彼得·阿佩尔 / 迈克尔...</td>\n",
       "      <td>剧情 / 动作 / 犯罪</td>\n",
       "      <td>法国</td>\n",
       "      <td>英语</td>\n",
       "      <td>110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>泰坦尼克号</td>\n",
       "      <td>1997</td>\n",
       "      <td>9.4</td>\n",
       "      <td>1706127.0</td>\n",
       "      <td>詹姆斯·卡梅隆</td>\n",
       "      <td>詹姆斯·卡梅隆</td>\n",
       "      <td>莱昂纳多·迪卡普里奥 / 凯特·温丝莱特 / 比利·赞恩 / 凯西·贝茨 / 弗兰西丝·费舍...</td>\n",
       "      <td>剧情 / 爱情 / 灾难</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>194.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>257</th>\n",
       "      <td>浪潮</td>\n",
       "      <td>2008</td>\n",
       "      <td>8.7</td>\n",
       "      <td>223511.0</td>\n",
       "      <td>丹尼斯·甘塞尔</td>\n",
       "      <td>丹尼斯·甘塞尔 / 彼得·图万斯 / 约翰尼·道金斯 / 罗恩·比恩巴赫 / 罗恩·琼斯</td>\n",
       "      <td>于尔根·福格尔 / 弗雷德里克·劳 / 马克思·雷迈特 / 詹妮弗·乌尔里希 / 克里斯蒂安...</td>\n",
       "      <td>剧情 / 惊悚</td>\n",
       "      <td>NaN</td>\n",
       "      <td>德语</td>\n",
       "      <td>107.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>258</th>\n",
       "      <td>小萝莉的猴神大叔</td>\n",
       "      <td>2015</td>\n",
       "      <td>8.4</td>\n",
       "      <td>404886.0</td>\n",
       "      <td>卡比尔·汗</td>\n",
       "      <td>卡比尔·汗 / 维杰耶德拉·普拉萨德</td>\n",
       "      <td>萨尔曼·汗 / 哈莎莉·马洛特拉 / 卡琳娜·卡普尔 / 纳瓦祖丁·席迪圭 / 欧姆·普瑞 ...</td>\n",
       "      <td>剧情 / 喜剧 / 动作</td>\n",
       "      <td>印度</td>\n",
       "      <td>印地语</td>\n",
       "      <td>159.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>259</th>\n",
       "      <td>追随</td>\n",
       "      <td>1998</td>\n",
       "      <td>8.9</td>\n",
       "      <td>149521.0</td>\n",
       "      <td>克里斯托弗·诺兰</td>\n",
       "      <td>克里斯托弗·诺兰</td>\n",
       "      <td>杰里米·西奥伯德 / 亚历克斯·霍 / 露西·拉塞尔 / 约翰·诺兰 / 迪克·布拉德塞尔 ...</td>\n",
       "      <td>悬疑 / 惊悚 / 犯罪</td>\n",
       "      <td>英国</td>\n",
       "      <td>英语</td>\n",
       "      <td>69.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260</th>\n",
       "      <td>网络谜踪</td>\n",
       "      <td>2018</td>\n",
       "      <td>8.6</td>\n",
       "      <td>430811.0</td>\n",
       "      <td>阿尼什·查甘蒂</td>\n",
       "      <td>阿尼什·查甘蒂 / 赛弗·奥哈尼安</td>\n",
       "      <td>约翰·赵 / 米切尔·拉 / 黛博拉·梅辛 / 约瑟夫·李 / 萨拉·米博·孙 / 亚历克丝...</td>\n",
       "      <td>剧情 / 悬疑 / 惊悚 / 犯罪</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>102.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261</th>\n",
       "      <td>黑鹰坠落</td>\n",
       "      <td>2001</td>\n",
       "      <td>8.7</td>\n",
       "      <td>239402.0</td>\n",
       "      <td>雷德利·斯科特</td>\n",
       "      <td>肯·诺兰 / 马克·鲍登</td>\n",
       "      <td>乔什·哈奈特 / 伊万·麦克格雷格 / 汤姆·塞兹摩尔 / 金·寇兹 / 艾文·布莱纳 / ...</td>\n",
       "      <td>动作 / 历史 / 战争</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>144.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           片名  上映年份   评分       评价人数        导演  \\\n",
       "0      肖申克的救赎  1994  9.7  2317937.0  弗兰克·德拉邦特   \n",
       "1        霸王别姬  1993  9.6  1720638.0       陈凯歌   \n",
       "2        阿甘正传  1994  9.5  1743966.0  罗伯特·泽米吉斯   \n",
       "3     这个杀手不太冷  1994  9.4  1922740.0     吕克·贝松   \n",
       "4       泰坦尼克号  1997  9.4  1706127.0   詹姆斯·卡梅隆   \n",
       "257        浪潮  2008  8.7   223511.0   丹尼斯·甘塞尔   \n",
       "258  小萝莉的猴神大叔  2015  8.4   404886.0     卡比尔·汗   \n",
       "259        追随  1998  8.9   149521.0  克里斯托弗·诺兰   \n",
       "260      网络谜踪  2018  8.6   430811.0   阿尼什·查甘蒂   \n",
       "261      黑鹰坠落  2001  8.7   239402.0   雷德利·斯科特   \n",
       "\n",
       "                                               编剧  \\\n",
       "0                                弗兰克·德拉邦特 / 斯蒂芬·金   \n",
       "1                                        芦苇 / 李碧华   \n",
       "2                                艾瑞克·罗斯 / 温斯顿·格鲁姆   \n",
       "3                                           吕克·贝松   \n",
       "4                                         詹姆斯·卡梅隆   \n",
       "257  丹尼斯·甘塞尔 / 彼得·图万斯 / 约翰尼·道金斯 / 罗恩·比恩巴赫 / 罗恩·琼斯   \n",
       "258                            卡比尔·汗 / 维杰耶德拉·普拉萨德   \n",
       "259                                      克里斯托弗·诺兰   \n",
       "260                             阿尼什·查甘蒂 / 赛弗·奥哈尼安   \n",
       "261                                  肯·诺兰 / 马克·鲍登   \n",
       "\n",
       "                                                    主演                 类型  \\\n",
       "0    蒂姆·罗宾斯 / 摩根·弗里曼 / 鲍勃·冈顿 / 威廉姆·赛德勒 / 克兰西·布朗 / 吉...            剧情 / 犯罪   \n",
       "1    张国荣 / 张丰毅 / 巩俐 / 葛优 / 英达 / 蒋雯丽 / 吴大维 / 吕齐 / 雷汉...       剧情 / 爱情 / 同性   \n",
       "2    汤姆·汉克斯 / 罗宾·怀特 / 加里·西尼斯 / 麦凯尔泰·威廉逊 / 莎莉·菲尔德 / ...            剧情 / 爱情   \n",
       "3    让·雷诺 / 娜塔莉·波特曼 / 加里·奥德曼 / 丹尼·爱罗 / 彼得·阿佩尔 / 迈克尔...       剧情 / 动作 / 犯罪   \n",
       "4    莱昂纳多·迪卡普里奥 / 凯特·温丝莱特 / 比利·赞恩 / 凯西·贝茨 / 弗兰西丝·费舍...       剧情 / 爱情 / 灾难   \n",
       "257  于尔根·福格尔 / 弗雷德里克·劳 / 马克思·雷迈特 / 詹妮弗·乌尔里希 / 克里斯蒂安...            剧情 / 惊悚   \n",
       "258  萨尔曼·汗 / 哈莎莉·马洛特拉 / 卡琳娜·卡普尔 / 纳瓦祖丁·席迪圭 / 欧姆·普瑞 ...       剧情 / 喜剧 / 动作   \n",
       "259  杰里米·西奥伯德 / 亚历克斯·霍 / 露西·拉塞尔 / 约翰·诺兰 / 迪克·布拉德塞尔 ...       悬疑 / 惊悚 / 犯罪   \n",
       "260  约翰·赵 / 米切尔·拉 / 黛博拉·梅辛 / 约瑟夫·李 / 萨拉·米博·孙 / 亚历克丝...  剧情 / 悬疑 / 惊悚 / 犯罪   \n",
       "261  乔什·哈奈特 / 伊万·麦克格雷格 / 汤姆·塞兹摩尔 / 金·寇兹 / 艾文·布莱纳 / ...       动作 / 历史 / 战争   \n",
       "\n",
       "    国家/地区     语言  时长(分钟)  \n",
       "0      美国     英语   142.0  \n",
       "1      中国  汉语普通话   171.0  \n",
       "2      美国     英语   142.0  \n",
       "3      法国    英语    110.0  \n",
       "4      美国    英语    194.0  \n",
       "257   NaN     德语   107.0  \n",
       "258    印度   印地语    159.0  \n",
       "259    英国     英语    69.0  \n",
       "260    美国     英语   102.0  \n",
       "261    美国    英语    144.0  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[np.r_[0:5,-5:0]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4 - 查看数据基本信息\n",
    "\n",
    "看看数据类型，有无缺失值什么的"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 262 entries, 0 to 261\n",
      "Data columns (total 11 columns):\n",
      " #   Column  Non-Null Count  Dtype  \n",
      "---  ------  --------------  -----  \n",
      " 0   片名      262 non-null    object \n",
      " 1   上映年份    262 non-null    int64  \n",
      " 2   评分      257 non-null    float64\n",
      " 3   评价人数    259 non-null    float64\n",
      " 4   导演      262 non-null    object \n",
      " 5   编剧      262 non-null    object \n",
      " 6   主演      262 non-null    object \n",
      " 7   类型      262 non-null    object \n",
      " 8   国家/地区   256 non-null    object \n",
      " 9   语言      256 non-null    object \n",
      " 10  时长(分钟)  256 non-null    float64\n",
      "dtypes: float64(3), int64(1), object(7)\n",
      "memory usage: 22.6+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5 - 查看数据统计信息｜数值\n",
    "\n",
    "查看 **数值型** 列的统计信息，计数、均值什么的"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>片名</th>\n",
       "      <th>上映年份</th>\n",
       "      <th>评分</th>\n",
       "      <th>评价人数</th>\n",
       "      <th>导演</th>\n",
       "      <th>编剧</th>\n",
       "      <th>主演</th>\n",
       "      <th>类型</th>\n",
       "      <th>国家/地区</th>\n",
       "      <th>语言</th>\n",
       "      <th>时长(分钟)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>262</td>\n",
       "      <td>262.000000</td>\n",
       "      <td>257.000000</td>\n",
       "      <td>2.590000e+02</td>\n",
       "      <td>262</td>\n",
       "      <td>262</td>\n",
       "      <td>262</td>\n",
       "      <td>262</td>\n",
       "      <td>256</td>\n",
       "      <td>256</td>\n",
       "      <td>256.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>249</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>180</td>\n",
       "      <td>221</td>\n",
       "      <td>249</td>\n",
       "      <td>120</td>\n",
       "      <td>20</td>\n",
       "      <td>26</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>无人知晓</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>是枝裕和</td>\n",
       "      <td>是枝裕和</td>\n",
       "      <td>柳乐优弥 / 北浦爱 / 木村飞影 / 清水萌萌子 / 韩英惠 / 江原由希子 / 串田和美...</td>\n",
       "      <td>剧情</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>24</td>\n",
       "      <td>111</td>\n",
       "      <td>72</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2000.599237</td>\n",
       "      <td>8.907782</td>\n",
       "      <td>5.776317e+05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>121.828125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>NaN</td>\n",
       "      <td>15.572709</td>\n",
       "      <td>0.262682</td>\n",
       "      <td>3.676709e+05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28.078073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1931.000000</td>\n",
       "      <td>8.400000</td>\n",
       "      <td>1.064620e+05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>45.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1995.000000</td>\n",
       "      <td>8.700000</td>\n",
       "      <td>3.353075e+05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>101.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2004.000000</td>\n",
       "      <td>8.900000</td>\n",
       "      <td>4.799490e+05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>118.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2011.000000</td>\n",
       "      <td>9.100000</td>\n",
       "      <td>6.932305e+05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>136.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2019.000000</td>\n",
       "      <td>9.700000</td>\n",
       "      <td>2.317937e+06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>237.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          片名         上映年份          评分          评价人数    导演    编剧  \\\n",
       "count    262   262.000000  257.000000  2.590000e+02   262   262   \n",
       "unique   249          NaN         NaN           NaN   180   221   \n",
       "top     无人知晓          NaN         NaN           NaN  是枝裕和  是枝裕和   \n",
       "freq       5          NaN         NaN           NaN     8     7   \n",
       "mean     NaN  2000.599237    8.907782  5.776317e+05   NaN   NaN   \n",
       "std      NaN    15.572709    0.262682  3.676709e+05   NaN   NaN   \n",
       "min      NaN  1931.000000    8.400000  1.064620e+05   NaN   NaN   \n",
       "25%      NaN  1995.000000    8.700000  3.353075e+05   NaN   NaN   \n",
       "50%      NaN  2004.000000    8.900000  4.799490e+05   NaN   NaN   \n",
       "75%      NaN  2011.000000    9.100000  6.932305e+05   NaN   NaN   \n",
       "max      NaN  2019.000000    9.700000  2.317937e+06   NaN   NaN   \n",
       "\n",
       "                                                       主演   类型 国家/地区   语言  \\\n",
       "count                                                 262  262   256  256   \n",
       "unique                                                249  120    20   26   \n",
       "top     柳乐优弥 / 北浦爱 / 木村飞影 / 清水萌萌子 / 韩英惠 / 江原由希子 / 串田和美...   剧情    美国  英语    \n",
       "freq                                                    5   24   111   72   \n",
       "mean                                                  NaN  NaN   NaN  NaN   \n",
       "std                                                   NaN  NaN   NaN  NaN   \n",
       "min                                                   NaN  NaN   NaN  NaN   \n",
       "25%                                                   NaN  NaN   NaN  NaN   \n",
       "50%                                                   NaN  NaN   NaN  NaN   \n",
       "75%                                                   NaN  NaN   NaN  NaN   \n",
       "max                                                   NaN  NaN   NaN  NaN   \n",
       "\n",
       "            时长(分钟)  \n",
       "count   256.000000  \n",
       "unique         NaN  \n",
       "top            NaN  \n",
       "freq           NaN  \n",
       "mean    121.828125  \n",
       "std      28.078073  \n",
       "min      45.000000  \n",
       "25%     101.750000  \n",
       "50%     118.000000  \n",
       "75%     136.000000  \n",
       "max     237.000000  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe(include='all')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6 - 查看数据统计信息｜离散\n",
    "\n",
    "查看 **离散型** 列的统计信息，计数、频率什么"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 7 - 查看数据统计信息｜整体\n",
    "\n",
    "查看 **全部** 列的统计信息"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>评分</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>262.000000</td>\n",
       "      <td>257.000000</td>\n",
       "      <td>2.590000e+02</td>\n",
       "      <td>256.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2000.599237</td>\n",
       "      <td>8.907782</td>\n",
       "      <td>5.776317e+05</td>\n",
       "      <td>121.828125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>15.572709</td>\n",
       "      <td>0.262682</td>\n",
       "      <td>3.676709e+05</td>\n",
       "      <td>28.078073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1931.000000</td>\n",
       "      <td>8.400000</td>\n",
       "      <td>1.064620e+05</td>\n",
       "      <td>45.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1995.000000</td>\n",
       "      <td>8.700000</td>\n",
       "      <td>3.353075e+05</td>\n",
       "      <td>101.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2004.000000</td>\n",
       "      <td>8.900000</td>\n",
       "      <td>4.799490e+05</td>\n",
       "      <td>118.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2011.000000</td>\n",
       "      <td>9.100000</td>\n",
       "      <td>6.932305e+05</td>\n",
       "      <td>136.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2019.000000</td>\n",
       "      <td>9.700000</td>\n",
       "      <td>2.317937e+06</td>\n",
       "      <td>237.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              上映年份          评分          评价人数      时长(分钟)\n",
       "count   262.000000  257.000000  2.590000e+02  256.000000\n",
       "mean   2000.599237    8.907782  5.776317e+05  121.828125\n",
       "std      15.572709    0.262682  3.676709e+05   28.078073\n",
       "min    1931.000000    8.400000  1.064620e+05   45.000000\n",
       "25%    1995.000000    8.700000  3.353075e+05  101.750000\n",
       "50%    2004.000000    8.900000  4.799490e+05  118.000000\n",
       "75%    2011.000000    9.100000  6.932305e+05  136.000000\n",
       "max    2019.000000    9.700000  2.317937e+06  237.000000"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 缺失值处理"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 8 - 计算缺失值｜总计"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "通过上面的查看，我们发现部分列是存在缺失值的，那么先看看一共存在多少个缺失值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "26"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#list(df.isna().values.flat).count(True)\n",
    "df.isna().sum().sum()\n",
    "#df.isna().sum()  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 9 - 计算缺失值｜分列\n",
    "\n",
    "再看看具体每列有多少缺失值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "片名        0\n",
       "上映年份      0\n",
       "评分        5\n",
       "评价人数      3\n",
       "导演        0\n",
       "编剧        0\n",
       "主演        0\n",
       "类型        0\n",
       "国家/地区     6\n",
       "语言        6\n",
       "时长(分钟)    6\n",
       "dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#len(df) - df.count()\n",
    "df.isna().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 10 - 查看缺失值\n",
    "\n",
    "</br>\n",
    "\n",
    "为了后面更方便的处理缺失值，现在先看看全部缺失值所在的行"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>片名</th>\n",
       "      <th>上映年份</th>\n",
       "      <th>评分</th>\n",
       "      <th>评价人数</th>\n",
       "      <th>导演</th>\n",
       "      <th>编剧</th>\n",
       "      <th>主演</th>\n",
       "      <th>类型</th>\n",
       "      <th>国家/地区</th>\n",
       "      <th>语言</th>\n",
       "      <th>时长(分钟)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>千与千寻</td>\n",
       "      <td>2001</td>\n",
       "      <td>9.4</td>\n",
       "      <td>1822369.0</td>\n",
       "      <td>宫崎骏</td>\n",
       "      <td>宫崎骏</td>\n",
       "      <td>柊瑠美 / 入野自由 / 夏木真理 / 菅原文太 / 中村彰男 / 玉井夕海 / 神木隆之介...</td>\n",
       "      <td>剧情 / 动画 / 奇幻</td>\n",
       "      <td>日本</td>\n",
       "      <td>日语</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>海上钢琴师</td>\n",
       "      <td>1998</td>\n",
       "      <td>9.3</td>\n",
       "      <td>1371726.0</td>\n",
       "      <td>朱塞佩·托纳多雷</td>\n",
       "      <td>亚利桑德罗·巴里克 / 朱塞佩·托纳多雷</td>\n",
       "      <td>蒂姆·罗斯 / 普路特·泰勒·文斯 / 比尔·努恩 / 克兰伦斯·威廉姆斯三世 / 梅兰尼·...</td>\n",
       "      <td>剧情 / 音乐</td>\n",
       "      <td>意大利</td>\n",
       "      <td>NaN</td>\n",
       "      <td>165.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>熔炉</td>\n",
       "      <td>2011</td>\n",
       "      <td>9.3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>黄东赫</td>\n",
       "      <td>黄东赫 / 孔枝泳</td>\n",
       "      <td>孔刘 / 郑有美 / 金贤秀 / 郑仁絮 / 白承焕 / 张光 / 金民尚 / 林贤成 / ...</td>\n",
       "      <td>剧情</td>\n",
       "      <td>韩国</td>\n",
       "      <td>韩语</td>\n",
       "      <td>125.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>教父</td>\n",
       "      <td>1972</td>\n",
       "      <td>9.3</td>\n",
       "      <td>756991.0</td>\n",
       "      <td>弗朗西斯·福特·科波拉</td>\n",
       "      <td>马里奥·普佐 / 弗朗西斯·福特·科波拉</td>\n",
       "      <td>马龙·白兰度 / 阿尔·帕西诺 / 詹姆斯·肯恩 / 理查德·卡斯特尔诺 / 罗伯特·杜瓦尔...</td>\n",
       "      <td>剧情 / 犯罪</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>当幸福来敲门</td>\n",
       "      <td>2006</td>\n",
       "      <td>9.1</td>\n",
       "      <td>1237631.0</td>\n",
       "      <td>加布里埃莱·穆奇诺</td>\n",
       "      <td>斯蒂夫·康拉德</td>\n",
       "      <td>威尔·史密斯 / 贾登·史密斯 / 坦迪·牛顿 / 布莱恩·豪威  / 詹姆斯·凯伦 / 丹...</td>\n",
       "      <td>剧情 / 家庭 / 传记</td>\n",
       "      <td>美国</td>\n",
       "      <td>NaN</td>\n",
       "      <td>117.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>龙猫</td>\n",
       "      <td>1988</td>\n",
       "      <td>9.2</td>\n",
       "      <td>1032307.0</td>\n",
       "      <td>宫崎骏</td>\n",
       "      <td>宫崎骏</td>\n",
       "      <td>日高法子 / 坂本千夏 / 糸井重里 / 岛本须美 / 北林谷荣 / 高木均 / 雨笠利幸 ...</td>\n",
       "      <td>动画 / 奇幻 / 冒险</td>\n",
       "      <td>日本</td>\n",
       "      <td>日语</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>乱世佳人</td>\n",
       "      <td>1939</td>\n",
       "      <td>9.3</td>\n",
       "      <td>556888.0</td>\n",
       "      <td>维克多·弗莱明 / 乔治·库克 / 山姆·伍德</td>\n",
       "      <td>玛格丽特·米歇尔 / 西德尼·霍华德 / 奥利弗·H·P·加勒特 / 本·赫克特 / 乔·斯...</td>\n",
       "      <td>费雯·丽 / 克拉克·盖博 / 奥利维娅·德哈维兰 / 托马斯·米切尔 / 芭芭拉·欧内尔 ...</td>\n",
       "      <td>剧情 / 爱情 / 历史 / 战争</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>我不是药神</td>\n",
       "      <td>2018</td>\n",
       "      <td>9.0</td>\n",
       "      <td>1696301.0</td>\n",
       "      <td>文牧野</td>\n",
       "      <td>韩家女 / 钟伟 / 文牧野</td>\n",
       "      <td>徐峥 / 王传君 / 周一围 / 谭卓 / 章宇 / 杨新鸣 / 王佳佳 / 王砚辉 / 贾...</td>\n",
       "      <td>剧情 / 喜剧</td>\n",
       "      <td>NaN</td>\n",
       "      <td>汉语普通话</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>狮子王</td>\n",
       "      <td>1994</td>\n",
       "      <td>9.0</td>\n",
       "      <td>665020.0</td>\n",
       "      <td>罗杰·阿勒斯 / 罗伯·明可夫</td>\n",
       "      <td>艾琳·梅琪 / 乔纳森·罗伯特  / 琳达·伍尔芙顿</td>\n",
       "      <td>乔纳森·泰勒·托马斯 / 马修·布罗德里克 / 杰瑞米·艾恩斯 / 詹姆斯·厄尔·琼斯 / ...</td>\n",
       "      <td>动画 / 歌舞 / 冒险</td>\n",
       "      <td>NaN</td>\n",
       "      <td>英语</td>\n",
       "      <td>89.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>情书</td>\n",
       "      <td>1995</td>\n",
       "      <td>NaN</td>\n",
       "      <td>726751.0</td>\n",
       "      <td>岩井俊二</td>\n",
       "      <td>岩井俊二</td>\n",
       "      <td>中山美穗 / 丰川悦司 / 酒井美纪 / 柏原崇 / 范文雀 / 篠原胜之 / 铃木庆一 /...</td>\n",
       "      <td>剧情 / 爱情</td>\n",
       "      <td>日本</td>\n",
       "      <td>日语</td>\n",
       "      <td>117.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>蝴蝶效应</td>\n",
       "      <td>2004</td>\n",
       "      <td>NaN</td>\n",
       "      <td>751155.0</td>\n",
       "      <td>埃里克·布雷斯 / J·麦基·格鲁伯</td>\n",
       "      <td>J·麦基·格鲁伯 / 埃里克·布雷斯</td>\n",
       "      <td>阿什顿·库彻 / 梅洛拉·沃尔特斯 / 艾米·斯马特 / 埃尔登·汉森 / 威廉姆·李·斯科...</td>\n",
       "      <td>剧情 / 科幻 / 悬疑 / 惊悚</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>113.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>心灵捕手</td>\n",
       "      <td>1997</td>\n",
       "      <td>8.9</td>\n",
       "      <td>565379.0</td>\n",
       "      <td>格斯·范·桑特</td>\n",
       "      <td>本·阿弗莱克 / 马特·达蒙</td>\n",
       "      <td>马特·达蒙 / 罗宾·威廉姆斯 / 本·阿弗莱克 / 斯特兰·斯卡斯加德 / 明妮·德里弗 ...</td>\n",
       "      <td>剧情</td>\n",
       "      <td>美国</td>\n",
       "      <td>NaN</td>\n",
       "      <td>126.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>无人知晓</td>\n",
       "      <td>2004</td>\n",
       "      <td>9.1</td>\n",
       "      <td>233881.0</td>\n",
       "      <td>是枝裕和</td>\n",
       "      <td>是枝裕和</td>\n",
       "      <td>柳乐优弥 / 北浦爱 / 木村飞影 / 清水萌萌子 / 韩英惠 / 江原由希子 / 串田和美...</td>\n",
       "      <td>剧情</td>\n",
       "      <td>日本</td>\n",
       "      <td>日语</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>甜蜜蜜</td>\n",
       "      <td>1996</td>\n",
       "      <td>NaN</td>\n",
       "      <td>420172.0</td>\n",
       "      <td>陈可辛</td>\n",
       "      <td>岸西</td>\n",
       "      <td>黎明 / 张曼玉 / 杨恭如 / 曾志伟 / 杜可风 / 张同祖 / 诸慧荷 / 丁羽</td>\n",
       "      <td>剧情 / 爱情</td>\n",
       "      <td>中国</td>\n",
       "      <td>粤语</td>\n",
       "      <td>118.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>萤火之森</td>\n",
       "      <td>2011</td>\n",
       "      <td>8.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>大森贵弘</td>\n",
       "      <td>绿川幸</td>\n",
       "      <td>佐仓绫音 / 内山昂辉 / 辻亲八 / 山本兼平 / 后藤弘树 / 今井麻美</td>\n",
       "      <td>剧情 / 爱情 / 动画 / 奇幻</td>\n",
       "      <td>日本</td>\n",
       "      <td>日语</td>\n",
       "      <td>45.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>驯龙高手</td>\n",
       "      <td>2010</td>\n",
       "      <td>8.7</td>\n",
       "      <td>617312.0</td>\n",
       "      <td>迪恩·德布洛斯 / 克里斯·桑德斯</td>\n",
       "      <td>威廉姆·戴维斯 / 迪恩·德布洛斯 / 克里斯·桑德斯 / 葛蕾熙达·柯维尔</td>\n",
       "      <td>杰伊·巴鲁切尔 / 杰拉德·巴特勒 / 克雷格·费格森 / 亚美莉卡·费雷拉 / 乔纳·希尔...</td>\n",
       "      <td>动画 / 奇幻 / 冒险</td>\n",
       "      <td>美国</td>\n",
       "      <td>NaN</td>\n",
       "      <td>98.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>英雄本色</td>\n",
       "      <td>1986</td>\n",
       "      <td>8.7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>吴宇森</td>\n",
       "      <td>陈庆嘉 / 吴宇森 / 梁淑华</td>\n",
       "      <td>周润发 / 狄龙 / 张国荣 / 朱宝意 / 李子雄 / 田丰 / 吴宇森 / 曾江 / 成...</td>\n",
       "      <td>剧情 / 动作 / 犯罪</td>\n",
       "      <td>中国</td>\n",
       "      <td>粤语</td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>谍影重重3</td>\n",
       "      <td>2007</td>\n",
       "      <td>NaN</td>\n",
       "      <td>345352.0</td>\n",
       "      <td>保罗·格林格拉斯</td>\n",
       "      <td>托尼·吉尔罗伊 / 乔治·诺非 / 斯科特·Z·本恩斯</td>\n",
       "      <td>马特·达蒙 / 朱丽娅·斯蒂尔斯 / 大卫·斯特雷泽恩 / 斯科特·格伦 / 帕迪·康斯戴恩...</td>\n",
       "      <td>动作 / 悬疑 / 惊悚</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>115.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>头脑特工队</td>\n",
       "      <td>2015</td>\n",
       "      <td>NaN</td>\n",
       "      <td>478719.0</td>\n",
       "      <td>彼特·道格特 / 罗纳尔多·德尔·卡门</td>\n",
       "      <td>彼特·道格特 / 罗纳尔多·德尔·卡门 / 梅格·勒福夫 / 乔什·库雷 / 迈克尔·阿恩特...</td>\n",
       "      <td>艾米·波勒 / 菲利丝·史密斯 / 理查德·坎德 / 比尔·哈德尔 / 刘易斯·布莱克 / ...</td>\n",
       "      <td>喜剧 / 动画 / 冒险</td>\n",
       "      <td>美国</td>\n",
       "      <td>NaN</td>\n",
       "      <td>95.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>海街日记</td>\n",
       "      <td>2015</td>\n",
       "      <td>8.8</td>\n",
       "      <td>335964.0</td>\n",
       "      <td>是枝裕和</td>\n",
       "      <td>是枝裕和 / 吉田秋生</td>\n",
       "      <td>绫濑遥 / 长泽雅美 / 夏帆 / 广濑铃 / 大竹忍 / 堤真一 / 加濑亮 / 风吹淳 ...</td>\n",
       "      <td>剧情 / 家庭</td>\n",
       "      <td>NaN</td>\n",
       "      <td>日语</td>\n",
       "      <td>127.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>惊魂记</td>\n",
       "      <td>1960</td>\n",
       "      <td>9.0</td>\n",
       "      <td>202622.0</td>\n",
       "      <td>阿尔弗雷德·希区柯克</td>\n",
       "      <td>约瑟夫·斯蒂凡诺 / 罗伯特·布洛克</td>\n",
       "      <td>安东尼·博金斯 / 维拉·迈尔斯 / 约翰·加文 / 珍妮特·利 / 马丁·鲍尔萨姆 / 约...</td>\n",
       "      <td>悬疑 / 惊悚 / 恐怖</td>\n",
       "      <td>NaN</td>\n",
       "      <td>英语</td>\n",
       "      <td>109.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>黑天鹅</td>\n",
       "      <td>2010</td>\n",
       "      <td>8.6</td>\n",
       "      <td>680102.0</td>\n",
       "      <td>达伦·阿伦诺夫斯基</td>\n",
       "      <td>安德雷斯·海因斯 / 马克·海曼 / 约翰·J·麦克劳克林</td>\n",
       "      <td>娜塔莉·波特曼 / 米拉·库尼斯 / 文森特·卡索 / 芭芭拉·赫希 / 薇诺娜·瑞德 / ...</td>\n",
       "      <td>剧情 / 惊悚</td>\n",
       "      <td>美国</td>\n",
       "      <td>NaN</td>\n",
       "      <td>108.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>冰川时代</td>\n",
       "      <td>2002</td>\n",
       "      <td>8.6</td>\n",
       "      <td>507275.0</td>\n",
       "      <td>卡洛斯·沙尔丹哈 / 克里斯·韦奇</td>\n",
       "      <td>迈克尔·伯格  / 迈克尔·J·威尔森 / 彼得·阿克曼</td>\n",
       "      <td>雷·罗马诺 / 约翰·雷吉扎莫 / 丹尼斯·利瑞 / 杰克·布莱克</td>\n",
       "      <td>喜剧 / 动画 / 冒险</td>\n",
       "      <td>NaN</td>\n",
       "      <td>英语</td>\n",
       "      <td>81.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>257</th>\n",
       "      <td>浪潮</td>\n",
       "      <td>2008</td>\n",
       "      <td>8.7</td>\n",
       "      <td>223511.0</td>\n",
       "      <td>丹尼斯·甘塞尔</td>\n",
       "      <td>丹尼斯·甘塞尔 / 彼得·图万斯 / 约翰尼·道金斯 / 罗恩·比恩巴赫 / 罗恩·琼斯</td>\n",
       "      <td>于尔根·福格尔 / 弗雷德里克·劳 / 马克思·雷迈特 / 詹妮弗·乌尔里希 / 克里斯蒂安...</td>\n",
       "      <td>剧情 / 惊悚</td>\n",
       "      <td>NaN</td>\n",
       "      <td>德语</td>\n",
       "      <td>107.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         片名  上映年份   评分       评价人数                       导演  \\\n",
       "6      千与千寻  2001  9.4  1822369.0                      宫崎骏   \n",
       "12    海上钢琴师  1998  9.3  1371726.0                 朱塞佩·托纳多雷   \n",
       "19       熔炉  2011  9.3        NaN                      黄东赫   \n",
       "20       教父  1972  9.3   756991.0              弗朗西斯·福特·科波拉   \n",
       "21   当幸福来敲门  2006  9.1  1237631.0                加布里埃莱·穆奇诺   \n",
       "22       龙猫  1988  9.2  1032307.0                      宫崎骏   \n",
       "31     乱世佳人  1939  9.3   556888.0  维克多·弗莱明 / 乔治·库克 / 山姆·伍德   \n",
       "43    我不是药神  2018  9.0  1696301.0                      文牧野   \n",
       "53      狮子王  1994  9.0   665020.0          罗杰·阿勒斯 / 罗伯·明可夫   \n",
       "73       情书  1995  NaN   726751.0                     岩井俊二   \n",
       "81     蝴蝶效应  2004  NaN   751155.0       埃里克·布雷斯 / J·麦基·格鲁伯   \n",
       "82     心灵捕手  1997  8.9   565379.0                  格斯·范·桑特   \n",
       "113    无人知晓  2004  9.1   233881.0                     是枝裕和   \n",
       "133     甜蜜蜜  1996  NaN   420172.0                      陈可辛   \n",
       "135    萤火之森  2011  8.9        NaN                     大森贵弘   \n",
       "139    驯龙高手  2010  8.7   617312.0        迪恩·德布洛斯 / 克里斯·桑德斯   \n",
       "166    英雄本色  1986  8.7        NaN                      吴宇森   \n",
       "170   谍影重重3  2007  NaN   345352.0                 保罗·格林格拉斯   \n",
       "181   头脑特工队  2015  NaN   478719.0      彼特·道格特 / 罗纳尔多·德尔·卡门   \n",
       "189    海街日记  2015  8.8   335964.0                     是枝裕和   \n",
       "192     惊魂记  1960  9.0   202622.0               阿尔弗雷德·希区柯克   \n",
       "193     黑天鹅  2010  8.6   680102.0                达伦·阿伦诺夫斯基   \n",
       "197    冰川时代  2002  8.6   507275.0        卡洛斯·沙尔丹哈 / 克里斯·韦奇   \n",
       "257      浪潮  2008  8.7   223511.0                  丹尼斯·甘塞尔   \n",
       "\n",
       "                                                    编剧  \\\n",
       "6                                                  宫崎骏   \n",
       "12                                亚利桑德罗·巴里克 / 朱塞佩·托纳多雷   \n",
       "19                                           黄东赫 / 孔枝泳   \n",
       "20                                马里奥·普佐 / 弗朗西斯·福特·科波拉   \n",
       "21                                             斯蒂夫·康拉德   \n",
       "22                                                 宫崎骏   \n",
       "31   玛格丽特·米歇尔 / 西德尼·霍华德 / 奥利弗·H·P·加勒特 / 本·赫克特 / 乔·斯...   \n",
       "43                                      韩家女 / 钟伟 / 文牧野   \n",
       "53                          艾琳·梅琪 / 乔纳森·罗伯特  / 琳达·伍尔芙顿   \n",
       "73                                                岩井俊二   \n",
       "81                                  J·麦基·格鲁伯 / 埃里克·布雷斯   \n",
       "82                                      本·阿弗莱克 / 马特·达蒙   \n",
       "113                                               是枝裕和   \n",
       "133                                                 岸西   \n",
       "135                                                绿川幸   \n",
       "139             威廉姆·戴维斯 / 迪恩·德布洛斯 / 克里斯·桑德斯 / 葛蕾熙达·柯维尔   \n",
       "166                                    陈庆嘉 / 吴宇森 / 梁淑华   \n",
       "170                        托尼·吉尔罗伊 / 乔治·诺非 / 斯科特·Z·本恩斯   \n",
       "181  彼特·道格特 / 罗纳尔多·德尔·卡门 / 梅格·勒福夫 / 乔什·库雷 / 迈克尔·阿恩特...   \n",
       "189                                        是枝裕和 / 吉田秋生   \n",
       "192                                 约瑟夫·斯蒂凡诺 / 罗伯特·布洛克   \n",
       "193                      安德雷斯·海因斯 / 马克·海曼 / 约翰·J·麦克劳克林   \n",
       "197                       迈克尔·伯格  / 迈克尔·J·威尔森 / 彼得·阿克曼   \n",
       "257       丹尼斯·甘塞尔 / 彼得·图万斯 / 约翰尼·道金斯 / 罗恩·比恩巴赫 / 罗恩·琼斯   \n",
       "\n",
       "                                                    主演                 类型  \\\n",
       "6    柊瑠美 / 入野自由 / 夏木真理 / 菅原文太 / 中村彰男 / 玉井夕海 / 神木隆之介...       剧情 / 动画 / 奇幻   \n",
       "12   蒂姆·罗斯 / 普路特·泰勒·文斯 / 比尔·努恩 / 克兰伦斯·威廉姆斯三世 / 梅兰尼·...            剧情 / 音乐   \n",
       "19   孔刘 / 郑有美 / 金贤秀 / 郑仁絮 / 白承焕 / 张光 / 金民尚 / 林贤成 / ...                 剧情   \n",
       "20   马龙·白兰度 / 阿尔·帕西诺 / 詹姆斯·肯恩 / 理查德·卡斯特尔诺 / 罗伯特·杜瓦尔...            剧情 / 犯罪   \n",
       "21   威尔·史密斯 / 贾登·史密斯 / 坦迪·牛顿 / 布莱恩·豪威  / 詹姆斯·凯伦 / 丹...       剧情 / 家庭 / 传记   \n",
       "22   日高法子 / 坂本千夏 / 糸井重里 / 岛本须美 / 北林谷荣 / 高木均 / 雨笠利幸 ...       动画 / 奇幻 / 冒险   \n",
       "31   费雯·丽 / 克拉克·盖博 / 奥利维娅·德哈维兰 / 托马斯·米切尔 / 芭芭拉·欧内尔 ...  剧情 / 爱情 / 历史 / 战争   \n",
       "43   徐峥 / 王传君 / 周一围 / 谭卓 / 章宇 / 杨新鸣 / 王佳佳 / 王砚辉 / 贾...            剧情 / 喜剧   \n",
       "53   乔纳森·泰勒·托马斯 / 马修·布罗德里克 / 杰瑞米·艾恩斯 / 詹姆斯·厄尔·琼斯 / ...       动画 / 歌舞 / 冒险   \n",
       "73   中山美穗 / 丰川悦司 / 酒井美纪 / 柏原崇 / 范文雀 / 篠原胜之 / 铃木庆一 /...            剧情 / 爱情   \n",
       "81   阿什顿·库彻 / 梅洛拉·沃尔特斯 / 艾米·斯马特 / 埃尔登·汉森 / 威廉姆·李·斯科...  剧情 / 科幻 / 悬疑 / 惊悚   \n",
       "82   马特·达蒙 / 罗宾·威廉姆斯 / 本·阿弗莱克 / 斯特兰·斯卡斯加德 / 明妮·德里弗 ...                 剧情   \n",
       "113  柳乐优弥 / 北浦爱 / 木村飞影 / 清水萌萌子 / 韩英惠 / 江原由希子 / 串田和美...                 剧情   \n",
       "133        黎明 / 张曼玉 / 杨恭如 / 曾志伟 / 杜可风 / 张同祖 / 诸慧荷 / 丁羽            剧情 / 爱情   \n",
       "135             佐仓绫音 / 内山昂辉 / 辻亲八 / 山本兼平 / 后藤弘树 / 今井麻美  剧情 / 爱情 / 动画 / 奇幻   \n",
       "139  杰伊·巴鲁切尔 / 杰拉德·巴特勒 / 克雷格·费格森 / 亚美莉卡·费雷拉 / 乔纳·希尔...       动画 / 奇幻 / 冒险   \n",
       "166  周润发 / 狄龙 / 张国荣 / 朱宝意 / 李子雄 / 田丰 / 吴宇森 / 曾江 / 成...       剧情 / 动作 / 犯罪   \n",
       "170  马特·达蒙 / 朱丽娅·斯蒂尔斯 / 大卫·斯特雷泽恩 / 斯科特·格伦 / 帕迪·康斯戴恩...       动作 / 悬疑 / 惊悚   \n",
       "181  艾米·波勒 / 菲利丝·史密斯 / 理查德·坎德 / 比尔·哈德尔 / 刘易斯·布莱克 / ...       喜剧 / 动画 / 冒险   \n",
       "189  绫濑遥 / 长泽雅美 / 夏帆 / 广濑铃 / 大竹忍 / 堤真一 / 加濑亮 / 风吹淳 ...            剧情 / 家庭   \n",
       "192  安东尼·博金斯 / 维拉·迈尔斯 / 约翰·加文 / 珍妮特·利 / 马丁·鲍尔萨姆 / 约...       悬疑 / 惊悚 / 恐怖   \n",
       "193  娜塔莉·波特曼 / 米拉·库尼斯 / 文森特·卡索 / 芭芭拉·赫希 / 薇诺娜·瑞德 / ...            剧情 / 惊悚   \n",
       "197                  雷·罗马诺 / 约翰·雷吉扎莫 / 丹尼斯·利瑞 / 杰克·布莱克       喜剧 / 动画 / 冒险   \n",
       "257  于尔根·福格尔 / 弗雷德里克·劳 / 马克思·雷迈特 / 詹妮弗·乌尔里希 / 克里斯蒂安...            剧情 / 惊悚   \n",
       "\n",
       "    国家/地区      语言  时长(分钟)  \n",
       "6      日本      日语     NaN  \n",
       "12    意大利     NaN   165.0  \n",
       "19     韩国      韩语   125.0  \n",
       "20     美国     英语      NaN  \n",
       "21     美国     NaN   117.0  \n",
       "22     日本      日语     NaN  \n",
       "31     美国      英语     NaN  \n",
       "43    NaN  汉语普通话      NaN  \n",
       "53    NaN     英语     89.0  \n",
       "73     日本      日语   117.0  \n",
       "81     美国      英语   113.0  \n",
       "82     美国     NaN   126.0  \n",
       "113    日本      日语     NaN  \n",
       "133    中国     粤语    118.0  \n",
       "135    日本      日语    45.0  \n",
       "139    美国     NaN    98.0  \n",
       "166    中国     粤语     95.0  \n",
       "170    美国     英语    115.0  \n",
       "181    美国     NaN    95.0  \n",
       "189   NaN      日语   127.0  \n",
       "192   NaN      英语   109.0  \n",
       "193    美国     NaN   108.0  \n",
       "197   NaN     英语     81.0  \n",
       "257   NaN      德语   107.0  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# df[len(df.columns) - df.count(axis=1) > 0]\n",
    "# df[df.isna().any(axis = 1)].style.highlight_null()\n",
    "df[df.isna().any(axis = 1)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "微信搜索公众号「早起Python」，关注后可以获得更多资源！"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 11- 高亮缺失值"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "很明显，虽然上一题找到了全部缺失值所在的行，但是看的很头疼\n",
    "\n",
    "-> 现在将缺失值进行高亮进一步查看\n",
    "\n",
    "指路：<font color = '#E36C07'>**2-15**</font>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style type=\"text/css\">\n",
       "#T_6e85d_row0_col10, #T_6e85d_row1_col9, #T_6e85d_row2_col3, #T_6e85d_row3_col10, #T_6e85d_row4_col9, #T_6e85d_row5_col10, #T_6e85d_row6_col10, #T_6e85d_row7_col8, #T_6e85d_row7_col10, #T_6e85d_row8_col8, #T_6e85d_row9_col2, #T_6e85d_row10_col2, #T_6e85d_row11_col9, #T_6e85d_row12_col10, #T_6e85d_row13_col2, #T_6e85d_row14_col3, #T_6e85d_row15_col9, #T_6e85d_row16_col3, #T_6e85d_row17_col2, #T_6e85d_row18_col2, #T_6e85d_row18_col9, #T_6e85d_row19_col8, #T_6e85d_row20_col8, #T_6e85d_row21_col9, #T_6e85d_row22_col8, #T_6e85d_row23_col8 {\n",
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       "</style>\n",
       "<table id=\"T_6e85d_\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"blank level0\" >&nbsp;</th>\n",
       "      <th class=\"col_heading level0 col0\" >片名</th>\n",
       "      <th class=\"col_heading level0 col1\" >上映年份</th>\n",
       "      <th class=\"col_heading level0 col2\" >评分</th>\n",
       "      <th class=\"col_heading level0 col3\" >评价人数</th>\n",
       "      <th class=\"col_heading level0 col4\" >导演</th>\n",
       "      <th class=\"col_heading level0 col5\" >编剧</th>\n",
       "      <th class=\"col_heading level0 col6\" >主演</th>\n",
       "      <th class=\"col_heading level0 col7\" >类型</th>\n",
       "      <th class=\"col_heading level0 col8\" >国家/地区</th>\n",
       "      <th class=\"col_heading level0 col9\" >语言</th>\n",
       "      <th class=\"col_heading level0 col10\" >时长(分钟)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_6e85d_level0_row0\" class=\"row_heading level0 row0\" >6</th>\n",
       "      <td id=\"T_6e85d_row0_col0\" class=\"data row0 col0\" >千与千寻</td>\n",
       "      <td id=\"T_6e85d_row0_col1\" class=\"data row0 col1\" >2001</td>\n",
       "      <td id=\"T_6e85d_row0_col2\" class=\"data row0 col2\" >9.400000</td>\n",
       "      <td id=\"T_6e85d_row0_col3\" class=\"data row0 col3\" >1822369.000000</td>\n",
       "      <td id=\"T_6e85d_row0_col4\" class=\"data row0 col4\" >宫崎骏</td>\n",
       "      <td id=\"T_6e85d_row0_col5\" class=\"data row0 col5\" >宫崎骏</td>\n",
       "      <td id=\"T_6e85d_row0_col6\" class=\"data row0 col6\" >柊瑠美 / 入野自由 / 夏木真理 / 菅原文太 / 中村彰男 / 玉井夕海 / 神木隆之介 / 内藤刚志 / 泽口靖子 / 我修院达也 / 大泉洋 / 小林郁夫 / 上条恒彦 / 小野武彦</td>\n",
       "      <td id=\"T_6e85d_row0_col7\" class=\"data row0 col7\" >剧情 / 动画 / 奇幻</td>\n",
       "      <td id=\"T_6e85d_row0_col8\" class=\"data row0 col8\" >日本</td>\n",
       "      <td id=\"T_6e85d_row0_col9\" class=\"data row0 col9\" >日语</td>\n",
       "      <td id=\"T_6e85d_row0_col10\" class=\"data row0 col10\" >nan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6e85d_level0_row1\" class=\"row_heading level0 row1\" >12</th>\n",
       "      <td id=\"T_6e85d_row1_col0\" class=\"data row1 col0\" >海上钢琴师</td>\n",
       "      <td id=\"T_6e85d_row1_col1\" class=\"data row1 col1\" >1998</td>\n",
       "      <td id=\"T_6e85d_row1_col2\" class=\"data row1 col2\" >9.300000</td>\n",
       "      <td id=\"T_6e85d_row1_col3\" class=\"data row1 col3\" >1371726.000000</td>\n",
       "      <td id=\"T_6e85d_row1_col4\" class=\"data row1 col4\" >朱塞佩·托纳多雷</td>\n",
       "      <td id=\"T_6e85d_row1_col5\" class=\"data row1 col5\" >亚利桑德罗·巴里克 / 朱塞佩·托纳多雷</td>\n",
       "      <td id=\"T_6e85d_row1_col6\" class=\"data row1 col6\" >蒂姆·罗斯 / 普路特·泰勒·文斯 / 比尔·努恩 / 克兰伦斯·威廉姆斯三世 / 梅兰尼·蒂埃里 / 皮特·沃恩 / 尼尔·奥布赖恩 / 阿尔贝托·巴斯克斯 / 加布里埃莱·拉维亚 / 科里·巴克 / 西德尼·科尔 / Luigi De Luca / 尼古拉·迪·平托 / 费米·依鲁福祖 / 伊斯顿·盖奇 / 凯文·麦克纳利 / 布莱恩·普林格 / 沙拉·鲁宾 / 希思科特·威廉姆斯 / 阿妮妲·扎格利亚 / 安吉洛·迪洛雷塔</td>\n",
       "      <td id=\"T_6e85d_row1_col7\" class=\"data row1 col7\" >剧情 / 音乐</td>\n",
       "      <td id=\"T_6e85d_row1_col8\" class=\"data row1 col8\" >意大利</td>\n",
       "      <td id=\"T_6e85d_row1_col9\" class=\"data row1 col9\" >nan</td>\n",
       "      <td id=\"T_6e85d_row1_col10\" class=\"data row1 col10\" >165.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6e85d_level0_row2\" class=\"row_heading level0 row2\" >19</th>\n",
       "      <td id=\"T_6e85d_row2_col0\" class=\"data row2 col0\" >熔炉</td>\n",
       "      <td id=\"T_6e85d_row2_col1\" class=\"data row2 col1\" >2011</td>\n",
       "      <td id=\"T_6e85d_row2_col2\" class=\"data row2 col2\" >9.300000</td>\n",
       "      <td id=\"T_6e85d_row2_col3\" class=\"data row2 col3\" >nan</td>\n",
       "      <td id=\"T_6e85d_row2_col4\" class=\"data row2 col4\" >黄东赫</td>\n",
       "      <td id=\"T_6e85d_row2_col5\" class=\"data row2 col5\" >黄东赫 / 孔枝泳</td>\n",
       "      <td id=\"T_6e85d_row2_col6\" class=\"data row2 col6\" >孔刘 / 郑有美 / 金贤秀 / 郑仁絮 / 白承焕 / 张光 / 金民尚 / 林贤成 / 金周灵 / 严孝燮 / 全国焕 / 崔镇浩 / 金志映 / 严智星 / 许在浩 / 张素妍</td>\n",
       "      <td id=\"T_6e85d_row2_col7\" class=\"data row2 col7\" >剧情</td>\n",
       "      <td id=\"T_6e85d_row2_col8\" class=\"data row2 col8\" >韩国</td>\n",
       "      <td id=\"T_6e85d_row2_col9\" class=\"data row2 col9\" >韩语</td>\n",
       "      <td id=\"T_6e85d_row2_col10\" class=\"data row2 col10\" >125.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6e85d_level0_row3\" class=\"row_heading level0 row3\" >20</th>\n",
       "      <td id=\"T_6e85d_row3_col0\" class=\"data row3 col0\" >教父</td>\n",
       "      <td id=\"T_6e85d_row3_col1\" class=\"data row3 col1\" >1972</td>\n",
       "      <td id=\"T_6e85d_row3_col2\" class=\"data row3 col2\" >9.300000</td>\n",
       "      <td id=\"T_6e85d_row3_col3\" class=\"data row3 col3\" >756991.000000</td>\n",
       "      <td id=\"T_6e85d_row3_col4\" class=\"data row3 col4\" >弗朗西斯·福特·科波拉</td>\n",
       "      <td id=\"T_6e85d_row3_col5\" class=\"data row3 col5\" >马里奥·普佐 / 弗朗西斯·福特·科波拉</td>\n",
       "      <td id=\"T_6e85d_row3_col6\" class=\"data row3 col6\" >马龙·白兰度 / 阿尔·帕西诺 / 詹姆斯·肯恩 / 理查德·卡斯特尔诺 / 罗伯特·杜瓦尔 / 斯特林·海登 / 约翰·马利 / 理查德·康特 / 艾尔·勒提埃里 / 黛安·基顿 / 阿贝·维高达 / 塔莉娅·夏尔 / 吉亚尼·罗素 / 约翰·凯泽尔 / 鲁迪·邦德 / 兰尼·蒙大拿</td>\n",
       "      <td id=\"T_6e85d_row3_col7\" class=\"data row3 col7\" >剧情 / 犯罪</td>\n",
       "      <td id=\"T_6e85d_row3_col8\" class=\"data row3 col8\" >美国</td>\n",
       "      <td id=\"T_6e85d_row3_col9\" class=\"data row3 col9\" >英语 </td>\n",
       "      <td id=\"T_6e85d_row3_col10\" class=\"data row3 col10\" >nan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6e85d_level0_row4\" class=\"row_heading level0 row4\" >21</th>\n",
       "      <td id=\"T_6e85d_row4_col0\" class=\"data row4 col0\" >当幸福来敲门</td>\n",
       "      <td id=\"T_6e85d_row4_col1\" class=\"data row4 col1\" >2006</td>\n",
       "      <td id=\"T_6e85d_row4_col2\" class=\"data row4 col2\" >9.100000</td>\n",
       "      <td id=\"T_6e85d_row4_col3\" class=\"data row4 col3\" >1237631.000000</td>\n",
       "      <td id=\"T_6e85d_row4_col4\" class=\"data row4 col4\" >加布里埃莱·穆奇诺</td>\n",
       "      <td id=\"T_6e85d_row4_col5\" class=\"data row4 col5\" >斯蒂夫·康拉德</td>\n",
       "      <td id=\"T_6e85d_row4_col6\" class=\"data row4 col6\" >威尔·史密斯 / 贾登·史密斯 / 坦迪·牛顿 / 布莱恩·豪威  / 詹姆斯·凯伦 / 丹·卡斯泰兰尼塔 / 柯特·富勒 / 塔卡尤·费舍尔 / 凯文·韦斯特 / 乔治·张 / 戴维·迈克尔·西尔弗曼 / 多米尼克·博夫 / 杰弗·卡伦 / 乔伊芙·拉文 / 斯科特·克拉斯</td>\n",
       "      <td id=\"T_6e85d_row4_col7\" class=\"data row4 col7\" >剧情 / 家庭 / 传记</td>\n",
       "      <td id=\"T_6e85d_row4_col8\" class=\"data row4 col8\" >美国</td>\n",
       "      <td id=\"T_6e85d_row4_col9\" class=\"data row4 col9\" >nan</td>\n",
       "      <td id=\"T_6e85d_row4_col10\" class=\"data row4 col10\" >117.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6e85d_level0_row5\" class=\"row_heading level0 row5\" >22</th>\n",
       "      <td id=\"T_6e85d_row5_col0\" class=\"data row5 col0\" >龙猫</td>\n",
       "      <td id=\"T_6e85d_row5_col1\" class=\"data row5 col1\" >1988</td>\n",
       "      <td id=\"T_6e85d_row5_col2\" class=\"data row5 col2\" >9.200000</td>\n",
       "      <td id=\"T_6e85d_row5_col3\" class=\"data row5 col3\" >1032307.000000</td>\n",
       "      <td id=\"T_6e85d_row5_col4\" class=\"data row5 col4\" >宫崎骏</td>\n",
       "      <td id=\"T_6e85d_row5_col5\" class=\"data row5 col5\" >宫崎骏</td>\n",
       "      <td id=\"T_6e85d_row5_col6\" class=\"data row5 col6\" >日高法子 / 坂本千夏 / 糸井重里 / 岛本须美 / 北林谷荣 / 高木均 / 雨笠利幸 / 丸山裕子 / 广濑正志 / 鹫尾真知子 / 铃木玲子 / 千叶繁 / 龙田直树 / 鳕子 / 西村朋纮 / 石田光子 / 神代知衣 / 中村大树 / 水谷优子 / 平松晶子 / 大谷育江</td>\n",
       "      <td id=\"T_6e85d_row5_col7\" class=\"data row5 col7\" >动画 / 奇幻 / 冒险</td>\n",
       "      <td id=\"T_6e85d_row5_col8\" class=\"data row5 col8\" >日本</td>\n",
       "      <td id=\"T_6e85d_row5_col9\" class=\"data row5 col9\" >日语</td>\n",
       "      <td id=\"T_6e85d_row5_col10\" class=\"data row5 col10\" >nan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6e85d_level0_row6\" class=\"row_heading level0 row6\" >31</th>\n",
       "      <td id=\"T_6e85d_row6_col0\" class=\"data row6 col0\" >乱世佳人</td>\n",
       "      <td id=\"T_6e85d_row6_col1\" class=\"data row6 col1\" >1939</td>\n",
       "      <td id=\"T_6e85d_row6_col2\" class=\"data row6 col2\" >9.300000</td>\n",
       "      <td id=\"T_6e85d_row6_col3\" class=\"data row6 col3\" >556888.000000</td>\n",
       "      <td id=\"T_6e85d_row6_col4\" class=\"data row6 col4\" >维克多·弗莱明 / 乔治·库克 / 山姆·伍德</td>\n",
       "      <td id=\"T_6e85d_row6_col5\" class=\"data row6 col5\" >玛格丽特·米歇尔 / 西德尼·霍华德 / 奥利弗·H·P·加勒特 / 本·赫克特 / 乔·斯沃林 / 约翰·范·德鲁登</td>\n",
       "      <td id=\"T_6e85d_row6_col6\" class=\"data row6 col6\" >费雯·丽 / 克拉克·盖博 / 奥利维娅·德哈维兰 / 托马斯·米切尔 / 芭芭拉·欧内尔 / 伊夫林·凯耶斯 / 安·卢瑟福德 / 乔治·里弗斯 / 弗莱德·克莱恩 / 海蒂·麦克丹尼尔 / 奥斯卡·波尔克 / 巴特弗莱·麦昆 / 维克托·乔里 / 埃弗雷特·布朗 / 霍华德·C·希克曼 / 艾丽西亚·瑞特 / 莱斯利·霍华德 / 兰德·布鲁克斯 / 卡洛尔·奈 / 劳拉·霍普·克鲁斯 / 埃迪·安德森 / 哈里·达文波特 / 利昂娜·罗伯特 / 简·达威尔 / 欧娜·满森 / 保罗·赫斯特 / 伊莎贝尔·朱尔 / 卡米·金·肯伦 / 艾瑞克·林登 / J·M·克里根 / 沃德·邦德 / 莉莲·肯布尔-库珀</td>\n",
       "      <td id=\"T_6e85d_row6_col7\" class=\"data row6 col7\" >剧情 / 爱情 / 历史 / 战争</td>\n",
       "      <td id=\"T_6e85d_row6_col8\" class=\"data row6 col8\" >美国</td>\n",
       "      <td id=\"T_6e85d_row6_col9\" class=\"data row6 col9\" >英语</td>\n",
       "      <td id=\"T_6e85d_row6_col10\" class=\"data row6 col10\" >nan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6e85d_level0_row7\" class=\"row_heading level0 row7\" >43</th>\n",
       "      <td id=\"T_6e85d_row7_col0\" class=\"data row7 col0\" >我不是药神</td>\n",
       "      <td id=\"T_6e85d_row7_col1\" class=\"data row7 col1\" >2018</td>\n",
       "      <td id=\"T_6e85d_row7_col2\" class=\"data row7 col2\" >9.000000</td>\n",
       "      <td id=\"T_6e85d_row7_col3\" class=\"data row7 col3\" >1696301.000000</td>\n",
       "      <td id=\"T_6e85d_row7_col4\" class=\"data row7 col4\" >文牧野</td>\n",
       "      <td id=\"T_6e85d_row7_col5\" class=\"data row7 col5\" >韩家女 / 钟伟 / 文牧野</td>\n",
       "      <td id=\"T_6e85d_row7_col6\" class=\"data row7 col6\" >徐峥 / 王传君 / 周一围 / 谭卓 / 章宇 / 杨新鸣 / 王佳佳 / 王砚辉 / 贾晨飞 / 龚蓓苾 / 宁浩 / 李乃文 / 岳小军 / 苇青 / 富冠铭 / 巴拉特·巴蒂 / 喜利图 / 张海艳 / 朱耕佑</td>\n",
       "      <td id=\"T_6e85d_row7_col7\" class=\"data row7 col7\" >剧情 / 喜剧</td>\n",
       "      <td id=\"T_6e85d_row7_col8\" class=\"data row7 col8\" >nan</td>\n",
       "      <td id=\"T_6e85d_row7_col9\" class=\"data row7 col9\" >汉语普通话 </td>\n",
       "      <td id=\"T_6e85d_row7_col10\" class=\"data row7 col10\" >nan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6e85d_level0_row8\" class=\"row_heading level0 row8\" >53</th>\n",
       "      <td id=\"T_6e85d_row8_col0\" class=\"data row8 col0\" >狮子王</td>\n",
       "      <td id=\"T_6e85d_row8_col1\" class=\"data row8 col1\" >1994</td>\n",
       "      <td id=\"T_6e85d_row8_col2\" class=\"data row8 col2\" >9.000000</td>\n",
       "      <td id=\"T_6e85d_row8_col3\" class=\"data row8 col3\" >665020.000000</td>\n",
       "      <td id=\"T_6e85d_row8_col4\" class=\"data row8 col4\" >罗杰·阿勒斯 / 罗伯·明可夫</td>\n",
       "      <td id=\"T_6e85d_row8_col5\" class=\"data row8 col5\" >艾琳·梅琪 / 乔纳森·罗伯特  / 琳达·伍尔芙顿</td>\n",
       "      <td id=\"T_6e85d_row8_col6\" class=\"data row8 col6\" >乔纳森·泰勒·托马斯 / 马修·布罗德里克 / 杰瑞米·艾恩斯 / 詹姆斯·厄尔·琼斯 / 莫伊拉·凯利 / 内森·连恩 / 尼基塔·卡兰姆 / 厄尼·萨贝拉 / 乌比·戈德堡 / 罗温·艾金森</td>\n",
       "      <td id=\"T_6e85d_row8_col7\" class=\"data row8 col7\" >动画 / 歌舞 / 冒险</td>\n",
       "      <td id=\"T_6e85d_row8_col8\" class=\"data row8 col8\" >nan</td>\n",
       "      <td id=\"T_6e85d_row8_col9\" class=\"data row8 col9\" >英语 </td>\n",
       "      <td id=\"T_6e85d_row8_col10\" class=\"data row8 col10\" >89.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6e85d_level0_row9\" class=\"row_heading level0 row9\" >73</th>\n",
       "      <td id=\"T_6e85d_row9_col0\" class=\"data row9 col0\" >情书</td>\n",
       "      <td id=\"T_6e85d_row9_col1\" class=\"data row9 col1\" >1995</td>\n",
       "      <td id=\"T_6e85d_row9_col2\" class=\"data row9 col2\" >nan</td>\n",
       "      <td id=\"T_6e85d_row9_col3\" class=\"data row9 col3\" >726751.000000</td>\n",
       "      <td id=\"T_6e85d_row9_col4\" class=\"data row9 col4\" >岩井俊二</td>\n",
       "      <td id=\"T_6e85d_row9_col5\" class=\"data row9 col5\" >岩井俊二</td>\n",
       "      <td id=\"T_6e85d_row9_col6\" class=\"data row9 col6\" >中山美穗 / 丰川悦司 / 酒井美纪 / 柏原崇 / 范文雀 / 篠原胜之 / 铃木庆一 / 田口智朗 / 加贺麻理子 / 光石研 / 铃木兰兰 / 盐见三省 / 中村久美 / 梅田凡乃 / 长田江身子  / 小栗香织 / 神户浩 / 酒井敏也 / 山口诗史 / 山崎一 / 德井优 / 武藤寿美</td>\n",
       "      <td id=\"T_6e85d_row9_col7\" class=\"data row9 col7\" >剧情 / 爱情</td>\n",
       "      <td id=\"T_6e85d_row9_col8\" class=\"data row9 col8\" >日本</td>\n",
       "      <td id=\"T_6e85d_row9_col9\" class=\"data row9 col9\" >日语</td>\n",
       "      <td id=\"T_6e85d_row9_col10\" class=\"data row9 col10\" >117.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6e85d_level0_row10\" class=\"row_heading level0 row10\" >81</th>\n",
       "      <td id=\"T_6e85d_row10_col0\" class=\"data row10 col0\" >蝴蝶效应</td>\n",
       "      <td id=\"T_6e85d_row10_col1\" class=\"data row10 col1\" >2004</td>\n",
       "      <td id=\"T_6e85d_row10_col2\" class=\"data row10 col2\" >nan</td>\n",
       "      <td id=\"T_6e85d_row10_col3\" class=\"data row10 col3\" >751155.000000</td>\n",
       "      <td id=\"T_6e85d_row10_col4\" class=\"data row10 col4\" >埃里克·布雷斯 / J·麦基·格鲁伯</td>\n",
       "      <td id=\"T_6e85d_row10_col5\" class=\"data row10 col5\" >J·麦基·格鲁伯 / 埃里克·布雷斯</td>\n",
       "      <td id=\"T_6e85d_row10_col6\" class=\"data row10 col6\" >阿什顿·库彻 / 梅洛拉·沃尔特斯 / 艾米·斯马特 / 埃尔登·汉森 / 威廉姆·李·斯科特 / 约翰·帕特里克·阿梅多利 / 艾琳·戈洛瓦娅 / 凯文·G·施密特 / 杰西·詹姆斯 / 罗根·勒曼 / 莎拉·威多斯 / 杰克·凯斯 / 卡梅隆·布莱特 / 埃里克·斯托尔兹 / 考乐姆·吉斯·雷尼 / 凯文·杜兰</td>\n",
       "      <td id=\"T_6e85d_row10_col7\" class=\"data row10 col7\" >剧情 / 科幻 / 悬疑 / 惊悚</td>\n",
       "      <td id=\"T_6e85d_row10_col8\" class=\"data row10 col8\" >美国</td>\n",
       "      <td id=\"T_6e85d_row10_col9\" class=\"data row10 col9\" >英语</td>\n",
       "      <td id=\"T_6e85d_row10_col10\" class=\"data row10 col10\" >113.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6e85d_level0_row11\" class=\"row_heading level0 row11\" >82</th>\n",
       "      <td id=\"T_6e85d_row11_col0\" class=\"data row11 col0\" >心灵捕手</td>\n",
       "      <td id=\"T_6e85d_row11_col1\" class=\"data row11 col1\" >1997</td>\n",
       "      <td id=\"T_6e85d_row11_col2\" class=\"data row11 col2\" >8.900000</td>\n",
       "      <td id=\"T_6e85d_row11_col3\" class=\"data row11 col3\" >565379.000000</td>\n",
       "      <td id=\"T_6e85d_row11_col4\" class=\"data row11 col4\" >格斯·范·桑特</td>\n",
       "      <td id=\"T_6e85d_row11_col5\" class=\"data row11 col5\" >本·阿弗莱克 / 马特·达蒙</td>\n",
       "      <td id=\"T_6e85d_row11_col6\" class=\"data row11 col6\" >马特·达蒙 / 罗宾·威廉姆斯 / 本·阿弗莱克 / 斯特兰·斯卡斯加德 / 明妮·德里弗 / 卡西·阿弗莱克 / 科尔·豪瑟 / 约翰·迈顿 / 丹·华盛顿 / 艾莉森·福兰德 / 维克·萨海 / 史蒂文·科兹洛夫斯基 / 斯科特·威廉姆·文特斯 / 吉米·弗林 / 乔治·普林普顿 / 弗朗切斯科·克莱门特</td>\n",
       "      <td id=\"T_6e85d_row11_col7\" class=\"data row11 col7\" >剧情</td>\n",
       "      <td id=\"T_6e85d_row11_col8\" class=\"data row11 col8\" >美国</td>\n",
       "      <td id=\"T_6e85d_row11_col9\" class=\"data row11 col9\" >nan</td>\n",
       "      <td id=\"T_6e85d_row11_col10\" class=\"data row11 col10\" >126.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6e85d_level0_row12\" class=\"row_heading level0 row12\" >113</th>\n",
       "      <td id=\"T_6e85d_row12_col0\" class=\"data row12 col0\" >无人知晓</td>\n",
       "      <td id=\"T_6e85d_row12_col1\" class=\"data row12 col1\" >2004</td>\n",
       "      <td id=\"T_6e85d_row12_col2\" class=\"data row12 col2\" >9.100000</td>\n",
       "      <td id=\"T_6e85d_row12_col3\" class=\"data row12 col3\" >233881.000000</td>\n",
       "      <td id=\"T_6e85d_row12_col4\" class=\"data row12 col4\" >是枝裕和</td>\n",
       "      <td id=\"T_6e85d_row12_col5\" class=\"data row12 col5\" >是枝裕和</td>\n",
       "      <td id=\"T_6e85d_row12_col6\" class=\"data row12 col6\" >柳乐优弥 / 北浦爱 / 木村飞影 / 清水萌萌子 / 韩英惠 / 江原由希子 / 串田和美 / 冈元夕纪子 / 楯隆子 / 加濑亮 / 村野友希 / 田中庆太 / 木村佑一 / 远藤宪一 / 寺岛进 / 平泉成</td>\n",
       "      <td id=\"T_6e85d_row12_col7\" class=\"data row12 col7\" >剧情</td>\n",
       "      <td id=\"T_6e85d_row12_col8\" class=\"data row12 col8\" >日本</td>\n",
       "      <td id=\"T_6e85d_row12_col9\" class=\"data row12 col9\" >日语</td>\n",
       "      <td id=\"T_6e85d_row12_col10\" class=\"data row12 col10\" >nan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6e85d_level0_row13\" class=\"row_heading level0 row13\" >133</th>\n",
       "      <td id=\"T_6e85d_row13_col0\" class=\"data row13 col0\" >甜蜜蜜</td>\n",
       "      <td id=\"T_6e85d_row13_col1\" class=\"data row13 col1\" >1996</td>\n",
       "      <td id=\"T_6e85d_row13_col2\" class=\"data row13 col2\" >nan</td>\n",
       "      <td id=\"T_6e85d_row13_col3\" class=\"data row13 col3\" >420172.000000</td>\n",
       "      <td id=\"T_6e85d_row13_col4\" class=\"data row13 col4\" >陈可辛</td>\n",
       "      <td id=\"T_6e85d_row13_col5\" class=\"data row13 col5\" >岸西</td>\n",
       "      <td id=\"T_6e85d_row13_col6\" class=\"data row13 col6\" >黎明 / 张曼玉 / 杨恭如 / 曾志伟 / 杜可风 / 张同祖 / 诸慧荷 / 丁羽</td>\n",
       "      <td id=\"T_6e85d_row13_col7\" class=\"data row13 col7\" >剧情 / 爱情</td>\n",
       "      <td id=\"T_6e85d_row13_col8\" class=\"data row13 col8\" >中国</td>\n",
       "      <td id=\"T_6e85d_row13_col9\" class=\"data row13 col9\" >粤语 </td>\n",
       "      <td id=\"T_6e85d_row13_col10\" class=\"data row13 col10\" >118.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6e85d_level0_row14\" class=\"row_heading level0 row14\" >135</th>\n",
       "      <td id=\"T_6e85d_row14_col0\" class=\"data row14 col0\" >萤火之森</td>\n",
       "      <td id=\"T_6e85d_row14_col1\" class=\"data row14 col1\" >2011</td>\n",
       "      <td id=\"T_6e85d_row14_col2\" class=\"data row14 col2\" >8.900000</td>\n",
       "      <td id=\"T_6e85d_row14_col3\" class=\"data row14 col3\" >nan</td>\n",
       "      <td id=\"T_6e85d_row14_col4\" class=\"data row14 col4\" >大森贵弘</td>\n",
       "      <td id=\"T_6e85d_row14_col5\" class=\"data row14 col5\" >绿川幸</td>\n",
       "      <td id=\"T_6e85d_row14_col6\" class=\"data row14 col6\" >佐仓绫音 / 内山昂辉 / 辻亲八 / 山本兼平 / 后藤弘树 / 今井麻美</td>\n",
       "      <td id=\"T_6e85d_row14_col7\" class=\"data row14 col7\" >剧情 / 爱情 / 动画 / 奇幻</td>\n",
       "      <td id=\"T_6e85d_row14_col8\" class=\"data row14 col8\" >日本</td>\n",
       "      <td id=\"T_6e85d_row14_col9\" class=\"data row14 col9\" >日语</td>\n",
       "      <td id=\"T_6e85d_row14_col10\" class=\"data row14 col10\" >45.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6e85d_level0_row15\" class=\"row_heading level0 row15\" >139</th>\n",
       "      <td id=\"T_6e85d_row15_col0\" class=\"data row15 col0\" >驯龙高手</td>\n",
       "      <td id=\"T_6e85d_row15_col1\" class=\"data row15 col1\" >2010</td>\n",
       "      <td id=\"T_6e85d_row15_col2\" class=\"data row15 col2\" >8.700000</td>\n",
       "      <td id=\"T_6e85d_row15_col3\" class=\"data row15 col3\" >617312.000000</td>\n",
       "      <td id=\"T_6e85d_row15_col4\" class=\"data row15 col4\" >迪恩·德布洛斯 / 克里斯·桑德斯</td>\n",
       "      <td id=\"T_6e85d_row15_col5\" class=\"data row15 col5\" >威廉姆·戴维斯 / 迪恩·德布洛斯 / 克里斯·桑德斯 / 葛蕾熙达·柯维尔</td>\n",
       "      <td id=\"T_6e85d_row15_col6\" class=\"data row15 col6\" >杰伊·巴鲁切尔 / 杰拉德·巴特勒 / 克雷格·费格森 / 亚美莉卡·费雷拉 / 乔纳·希尔 / 克里斯托夫·梅兹-普莱瑟 / T·J·米勒 / 克里斯汀·韦格 / 罗宾·阿特金·唐斯 / 菲利普·麦格雷德 / 基隆·埃利奥特 / 阿什利·詹森 / 大卫·田纳特</td>\n",
       "      <td id=\"T_6e85d_row15_col7\" class=\"data row15 col7\" >动画 / 奇幻 / 冒险</td>\n",
       "      <td id=\"T_6e85d_row15_col8\" class=\"data row15 col8\" >美国</td>\n",
       "      <td id=\"T_6e85d_row15_col9\" class=\"data row15 col9\" >nan</td>\n",
       "      <td id=\"T_6e85d_row15_col10\" class=\"data row15 col10\" >98.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6e85d_level0_row16\" class=\"row_heading level0 row16\" >166</th>\n",
       "      <td id=\"T_6e85d_row16_col0\" class=\"data row16 col0\" >英雄本色</td>\n",
       "      <td id=\"T_6e85d_row16_col1\" class=\"data row16 col1\" >1986</td>\n",
       "      <td id=\"T_6e85d_row16_col2\" class=\"data row16 col2\" >8.700000</td>\n",
       "      <td id=\"T_6e85d_row16_col3\" class=\"data row16 col3\" >nan</td>\n",
       "      <td id=\"T_6e85d_row16_col4\" class=\"data row16 col4\" >吴宇森</td>\n",
       "      <td id=\"T_6e85d_row16_col5\" class=\"data row16 col5\" >陈庆嘉 / 吴宇森 / 梁淑华</td>\n",
       "      <td id=\"T_6e85d_row16_col6\" class=\"data row16 col6\" >周润发 / 狄龙 / 张国荣 / 朱宝意 / 李子雄 / 田丰 / 吴宇森 / 曾江 / 成奎安 / 徐克 / 陈志辉</td>\n",
       "      <td id=\"T_6e85d_row16_col7\" class=\"data row16 col7\" >剧情 / 动作 / 犯罪</td>\n",
       "      <td id=\"T_6e85d_row16_col8\" class=\"data row16 col8\" >中国</td>\n",
       "      <td id=\"T_6e85d_row16_col9\" class=\"data row16 col9\" >粤语 </td>\n",
       "      <td id=\"T_6e85d_row16_col10\" class=\"data row16 col10\" >95.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6e85d_level0_row17\" class=\"row_heading level0 row17\" >170</th>\n",
       "      <td id=\"T_6e85d_row17_col0\" class=\"data row17 col0\" >谍影重重3</td>\n",
       "      <td id=\"T_6e85d_row17_col1\" class=\"data row17 col1\" >2007</td>\n",
       "      <td id=\"T_6e85d_row17_col2\" class=\"data row17 col2\" >nan</td>\n",
       "      <td id=\"T_6e85d_row17_col3\" class=\"data row17 col3\" >345352.000000</td>\n",
       "      <td id=\"T_6e85d_row17_col4\" class=\"data row17 col4\" >保罗·格林格拉斯</td>\n",
       "      <td id=\"T_6e85d_row17_col5\" class=\"data row17 col5\" >托尼·吉尔罗伊 / 乔治·诺非 / 斯科特·Z·本恩斯</td>\n",
       "      <td id=\"T_6e85d_row17_col6\" class=\"data row17 col6\" >马特·达蒙 / 朱丽娅·斯蒂尔斯 / 大卫·斯特雷泽恩 / 斯科特·格伦 / 帕迪·康斯戴恩 / 埃德加·拉米雷兹 / 阿尔伯特·芬尼 / 琼·艾伦 / Tom Gallop / 克里·约翰逊 / 丹尼尔·布鲁赫 / 乔伊·安沙 / 科林·斯廷顿 / 丹·弗雷登堡 / Lucy Liemann</td>\n",
       "      <td id=\"T_6e85d_row17_col7\" class=\"data row17 col7\" >动作 / 悬疑 / 惊悚</td>\n",
       "      <td id=\"T_6e85d_row17_col8\" class=\"data row17 col8\" >美国</td>\n",
       "      <td id=\"T_6e85d_row17_col9\" class=\"data row17 col9\" >英语 </td>\n",
       "      <td id=\"T_6e85d_row17_col10\" class=\"data row17 col10\" >115.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6e85d_level0_row18\" class=\"row_heading level0 row18\" >181</th>\n",
       "      <td id=\"T_6e85d_row18_col0\" class=\"data row18 col0\" >头脑特工队</td>\n",
       "      <td id=\"T_6e85d_row18_col1\" class=\"data row18 col1\" >2015</td>\n",
       "      <td id=\"T_6e85d_row18_col2\" class=\"data row18 col2\" >nan</td>\n",
       "      <td id=\"T_6e85d_row18_col3\" class=\"data row18 col3\" >478719.000000</td>\n",
       "      <td id=\"T_6e85d_row18_col4\" class=\"data row18 col4\" >彼特·道格特 / 罗纳尔多·德尔·卡门</td>\n",
       "      <td id=\"T_6e85d_row18_col5\" class=\"data row18 col5\" >彼特·道格特 / 罗纳尔多·德尔·卡门 / 梅格·勒福夫 / 乔什·库雷 / 迈克尔·阿恩特 / 西蒙·里奇 / 鲍勃·彼德森 / 比尔·哈德尔 / 艾米·波勒</td>\n",
       "      <td id=\"T_6e85d_row18_col6\" class=\"data row18 col6\" >艾米·波勒 / 菲利丝·史密斯 / 理查德·坎德 / 比尔·哈德尔 / 刘易斯·布莱克 / 敏迪·卡灵 / 凯特林·迪亚斯 / 戴安·琳恩 / 凯尔·麦克拉克伦 / 波拉·庞德斯通 / 鲍比·莫尼汉 / 宝拉·佩尔 / 大卫·戈尔兹 / 弗兰克·奥兹 / 乔什·库雷 / 弗利 / 约翰·拉岑贝格 / 卡洛斯·阿拉斯拉奇 / 皮特·萨加尔 / 拉什达·琼斯 / 罗里·艾伦 / 约翰·齐甘 / 雪莉·琳恩 / 拉瑞恩·纽曼 / 帕丽斯·冯·戴克</td>\n",
       "      <td id=\"T_6e85d_row18_col7\" class=\"data row18 col7\" >喜剧 / 动画 / 冒险</td>\n",
       "      <td id=\"T_6e85d_row18_col8\" class=\"data row18 col8\" >美国</td>\n",
       "      <td id=\"T_6e85d_row18_col9\" class=\"data row18 col9\" >nan</td>\n",
       "      <td id=\"T_6e85d_row18_col10\" class=\"data row18 col10\" >95.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6e85d_level0_row19\" class=\"row_heading level0 row19\" >189</th>\n",
       "      <td id=\"T_6e85d_row19_col0\" class=\"data row19 col0\" >海街日记</td>\n",
       "      <td id=\"T_6e85d_row19_col1\" class=\"data row19 col1\" >2015</td>\n",
       "      <td id=\"T_6e85d_row19_col2\" class=\"data row19 col2\" >8.800000</td>\n",
       "      <td id=\"T_6e85d_row19_col3\" class=\"data row19 col3\" >335964.000000</td>\n",
       "      <td id=\"T_6e85d_row19_col4\" class=\"data row19 col4\" >是枝裕和</td>\n",
       "      <td id=\"T_6e85d_row19_col5\" class=\"data row19 col5\" >是枝裕和 / 吉田秋生</td>\n",
       "      <td id=\"T_6e85d_row19_col6\" class=\"data row19 col6\" >绫濑遥 / 长泽雅美 / 夏帆 / 广濑铃 / 大竹忍 / 堤真一 / 加濑亮 / 风吹淳 / 中川雅也 / 前田旺志郎  / 铃木亮平 / 坂口健太郎 / 树木希林</td>\n",
       "      <td id=\"T_6e85d_row19_col7\" class=\"data row19 col7\" >剧情 / 家庭</td>\n",
       "      <td id=\"T_6e85d_row19_col8\" class=\"data row19 col8\" >nan</td>\n",
       "      <td id=\"T_6e85d_row19_col9\" class=\"data row19 col9\" >日语</td>\n",
       "      <td id=\"T_6e85d_row19_col10\" class=\"data row19 col10\" >127.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6e85d_level0_row20\" class=\"row_heading level0 row20\" >192</th>\n",
       "      <td id=\"T_6e85d_row20_col0\" class=\"data row20 col0\" >惊魂记</td>\n",
       "      <td id=\"T_6e85d_row20_col1\" class=\"data row20 col1\" >1960</td>\n",
       "      <td id=\"T_6e85d_row20_col2\" class=\"data row20 col2\" >9.000000</td>\n",
       "      <td id=\"T_6e85d_row20_col3\" class=\"data row20 col3\" >202622.000000</td>\n",
       "      <td id=\"T_6e85d_row20_col4\" class=\"data row20 col4\" >阿尔弗雷德·希区柯克</td>\n",
       "      <td id=\"T_6e85d_row20_col5\" class=\"data row20 col5\" >约瑟夫·斯蒂凡诺 / 罗伯特·布洛克</td>\n",
       "      <td id=\"T_6e85d_row20_col6\" class=\"data row20 col6\" >安东尼·博金斯 / 维拉·迈尔斯 / 约翰·加文 / 珍妮特·利 / 马丁·鲍尔萨姆 / 约翰·麦克因泰 / 西蒙·奥克兰 / 弗兰克·艾伯森 / 帕特里夏·希区柯克 / 沃恩·泰勒 / 卢伦·塔特尔 / 约翰·安德森 / 莫特·米尔斯 / 吉特·卡森 / 维吉尼亚·格雷格 / 阿尔弗雷德·希区柯克 / 珍妮特·诺兰 / 罗伯特·奥斯本 / 海伦·华莱士 / Fletcher Allen / 沃尔特·培根 / 弗朗西斯·德塞尔斯 / 乔治·多克斯塔德 / 乔治·埃尔德雷奇 / 哈珀·弗莱厄蒂 / 萨姆·弗林特 / 弗兰克·基尔蒙德 / 泰德·奈特 / 帕特·麦卡弗里 / 汉斯-乔基姆·默比斯 / 弗雷德·谢威勒</td>\n",
       "      <td id=\"T_6e85d_row20_col7\" class=\"data row20 col7\" >悬疑 / 惊悚 / 恐怖</td>\n",
       "      <td id=\"T_6e85d_row20_col8\" class=\"data row20 col8\" >nan</td>\n",
       "      <td id=\"T_6e85d_row20_col9\" class=\"data row20 col9\" >英语</td>\n",
       "      <td id=\"T_6e85d_row20_col10\" class=\"data row20 col10\" >109.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6e85d_level0_row21\" class=\"row_heading level0 row21\" >193</th>\n",
       "      <td id=\"T_6e85d_row21_col0\" class=\"data row21 col0\" >黑天鹅</td>\n",
       "      <td id=\"T_6e85d_row21_col1\" class=\"data row21 col1\" >2010</td>\n",
       "      <td id=\"T_6e85d_row21_col2\" class=\"data row21 col2\" >8.600000</td>\n",
       "      <td id=\"T_6e85d_row21_col3\" class=\"data row21 col3\" >680102.000000</td>\n",
       "      <td id=\"T_6e85d_row21_col4\" class=\"data row21 col4\" >达伦·阿伦诺夫斯基</td>\n",
       "      <td id=\"T_6e85d_row21_col5\" class=\"data row21 col5\" >安德雷斯·海因斯 / 马克·海曼 / 约翰·J·麦克劳克林</td>\n",
       "      <td id=\"T_6e85d_row21_col6\" class=\"data row21 col6\" >娜塔莉·波特曼 / 米拉·库尼斯 / 文森特·卡索 / 芭芭拉·赫希 / 薇诺娜·瑞德 / 本杰明·米派德 / 克塞尼亚·索罗 / 克里斯汀娜·安娜波 / 詹妮特·蒙哥马利 / 塞巴斯蒂安·斯坦 / 托比·海明威 / 塞尔吉奥·托拉多 / 马克·马戈利斯 / 蒂娜·斯隆 / 亚伯拉罕·阿罗诺夫斯基 / 夏洛特·阿罗诺夫斯基 / 玛西娅·让·库尔茨 / 肖恩·奥哈根 / 克里斯托弗·加廷 / 黛博拉·奥夫纳 / 斯坦利·B·赫尔曼 / 库尔特·弗勒曼 / 帕特里克·赫辛格 / 莎拉·海伊</td>\n",
       "      <td id=\"T_6e85d_row21_col7\" class=\"data row21 col7\" >剧情 / 惊悚</td>\n",
       "      <td id=\"T_6e85d_row21_col8\" class=\"data row21 col8\" >美国</td>\n",
       "      <td id=\"T_6e85d_row21_col9\" class=\"data row21 col9\" >nan</td>\n",
       "      <td id=\"T_6e85d_row21_col10\" class=\"data row21 col10\" >108.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6e85d_level0_row22\" class=\"row_heading level0 row22\" >197</th>\n",
       "      <td id=\"T_6e85d_row22_col0\" class=\"data row22 col0\" >冰川时代</td>\n",
       "      <td id=\"T_6e85d_row22_col1\" class=\"data row22 col1\" >2002</td>\n",
       "      <td id=\"T_6e85d_row22_col2\" class=\"data row22 col2\" >8.600000</td>\n",
       "      <td id=\"T_6e85d_row22_col3\" class=\"data row22 col3\" >507275.000000</td>\n",
       "      <td id=\"T_6e85d_row22_col4\" class=\"data row22 col4\" >卡洛斯·沙尔丹哈 / 克里斯·韦奇</td>\n",
       "      <td id=\"T_6e85d_row22_col5\" class=\"data row22 col5\" >迈克尔·伯格  / 迈克尔·J·威尔森 / 彼得·阿克曼</td>\n",
       "      <td id=\"T_6e85d_row22_col6\" class=\"data row22 col6\" >雷·罗马诺 / 约翰·雷吉扎莫 / 丹尼斯·利瑞 / 杰克·布莱克</td>\n",
       "      <td id=\"T_6e85d_row22_col7\" class=\"data row22 col7\" >喜剧 / 动画 / 冒险</td>\n",
       "      <td id=\"T_6e85d_row22_col8\" class=\"data row22 col8\" >nan</td>\n",
       "      <td id=\"T_6e85d_row22_col9\" class=\"data row22 col9\" >英语 </td>\n",
       "      <td id=\"T_6e85d_row22_col10\" class=\"data row22 col10\" >81.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_6e85d_level0_row23\" class=\"row_heading level0 row23\" >257</th>\n",
       "      <td id=\"T_6e85d_row23_col0\" class=\"data row23 col0\" >浪潮</td>\n",
       "      <td id=\"T_6e85d_row23_col1\" class=\"data row23 col1\" >2008</td>\n",
       "      <td id=\"T_6e85d_row23_col2\" class=\"data row23 col2\" >8.700000</td>\n",
       "      <td id=\"T_6e85d_row23_col3\" class=\"data row23 col3\" >223511.000000</td>\n",
       "      <td id=\"T_6e85d_row23_col4\" class=\"data row23 col4\" >丹尼斯·甘塞尔</td>\n",
       "      <td id=\"T_6e85d_row23_col5\" class=\"data row23 col5\" >丹尼斯·甘塞尔 / 彼得·图万斯 / 约翰尼·道金斯 / 罗恩·比恩巴赫 / 罗恩·琼斯</td>\n",
       "      <td id=\"T_6e85d_row23_col6\" class=\"data row23 col6\" >于尔根·福格尔 / 弗雷德里克·劳 / 马克思·雷迈特 / 詹妮弗·乌尔里希 / 克里斯蒂安娜·保罗 / 雅各布·马琛茨 / 克里斯蒂娜·度·瑞格 / 埃利亚斯·穆巴里克 / 马克西米利安·福尔马尔 / 马克斯·毛夫</td>\n",
       "      <td id=\"T_6e85d_row23_col7\" class=\"data row23 col7\" >剧情 / 惊悚</td>\n",
       "      <td id=\"T_6e85d_row23_col8\" class=\"data row23 col8\" >nan</td>\n",
       "      <td id=\"T_6e85d_row23_col9\" class=\"data row23 col9\" >德语</td>\n",
       "      <td id=\"T_6e85d_row23_col10\" class=\"data row23 col10\" >107.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x7ff68b991748>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#df1 = df[len(df.columns) - df.count(axis=1) > 0]\n",
    "#df1.style.applymap(lambda x: \"color:red\" if pd.isna(x) else \"\" )\n",
    "#df1.style.highlight_null()\n",
    "\n",
    "df[df.isna().any(axis=1)].style.highlight_null()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 12 - 删除缺失值\n",
    "\n",
    "<br>\n",
    "\n",
    "处理缺失值最简单的方式，当然是将缺失值出现的行全部删掉～\n",
    "\n",
    "-> 现在，将缺失值出现的行全部删掉"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>片名</th>\n",
       "      <th>上映年份</th>\n",
       "      <th>评分</th>\n",
       "      <th>评价人数</th>\n",
       "      <th>导演</th>\n",
       "      <th>编剧</th>\n",
       "      <th>主演</th>\n",
       "      <th>类型</th>\n",
       "      <th>国家/地区</th>\n",
       "      <th>语言</th>\n",
       "      <th>时长(分钟)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>肖申克的救赎</td>\n",
       "      <td>1994</td>\n",
       "      <td>9.7</td>\n",
       "      <td>2317937.0</td>\n",
       "      <td>弗兰克·德拉邦特</td>\n",
       "      <td>弗兰克·德拉邦特 / 斯蒂芬·金</td>\n",
       "      <td>蒂姆·罗宾斯 / 摩根·弗里曼 / 鲍勃·冈顿 / 威廉姆·赛德勒 / 克兰西·布朗 / 吉...</td>\n",
       "      <td>剧情 / 犯罪</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>142.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>霸王别姬</td>\n",
       "      <td>1993</td>\n",
       "      <td>9.6</td>\n",
       "      <td>1720638.0</td>\n",
       "      <td>陈凯歌</td>\n",
       "      <td>芦苇 / 李碧华</td>\n",
       "      <td>张国荣 / 张丰毅 / 巩俐 / 葛优 / 英达 / 蒋雯丽 / 吴大维 / 吕齐 / 雷汉...</td>\n",
       "      <td>剧情 / 爱情 / 同性</td>\n",
       "      <td>中国</td>\n",
       "      <td>汉语普通话</td>\n",
       "      <td>171.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>阿甘正传</td>\n",
       "      <td>1994</td>\n",
       "      <td>9.5</td>\n",
       "      <td>1743966.0</td>\n",
       "      <td>罗伯特·泽米吉斯</td>\n",
       "      <td>艾瑞克·罗斯 / 温斯顿·格鲁姆</td>\n",
       "      <td>汤姆·汉克斯 / 罗宾·怀特 / 加里·西尼斯 / 麦凯尔泰·威廉逊 / 莎莉·菲尔德 / ...</td>\n",
       "      <td>剧情 / 爱情</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>142.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>这个杀手不太冷</td>\n",
       "      <td>1994</td>\n",
       "      <td>9.4</td>\n",
       "      <td>1922740.0</td>\n",
       "      <td>吕克·贝松</td>\n",
       "      <td>吕克·贝松</td>\n",
       "      <td>让·雷诺 / 娜塔莉·波特曼 / 加里·奥德曼 / 丹尼·爱罗 / 彼得·阿佩尔 / 迈克尔...</td>\n",
       "      <td>剧情 / 动作 / 犯罪</td>\n",
       "      <td>法国</td>\n",
       "      <td>英语</td>\n",
       "      <td>110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>泰坦尼克号</td>\n",
       "      <td>1997</td>\n",
       "      <td>9.4</td>\n",
       "      <td>1706127.0</td>\n",
       "      <td>詹姆斯·卡梅隆</td>\n",
       "      <td>詹姆斯·卡梅隆</td>\n",
       "      <td>莱昂纳多·迪卡普里奥 / 凯特·温丝莱特 / 比利·赞恩 / 凯西·贝茨 / 弗兰西丝·费舍...</td>\n",
       "      <td>剧情 / 爱情 / 灾难</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>194.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256</th>\n",
       "      <td>聚焦</td>\n",
       "      <td>2015</td>\n",
       "      <td>8.8</td>\n",
       "      <td>230899.0</td>\n",
       "      <td>汤姆·麦卡锡</td>\n",
       "      <td>乔希·辛格 / 汤姆·麦卡锡</td>\n",
       "      <td>马克·鲁弗洛 / 迈克尔·基顿 / 瑞秋·麦克亚当斯 / 列维·施瑞博尔 / 约翰·斯拉特里...</td>\n",
       "      <td>剧情 / 传记</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>128.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>258</th>\n",
       "      <td>小萝莉的猴神大叔</td>\n",
       "      <td>2015</td>\n",
       "      <td>8.4</td>\n",
       "      <td>404886.0</td>\n",
       "      <td>卡比尔·汗</td>\n",
       "      <td>卡比尔·汗 / 维杰耶德拉·普拉萨德</td>\n",
       "      <td>萨尔曼·汗 / 哈莎莉·马洛特拉 / 卡琳娜·卡普尔 / 纳瓦祖丁·席迪圭 / 欧姆·普瑞 ...</td>\n",
       "      <td>剧情 / 喜剧 / 动作</td>\n",
       "      <td>印度</td>\n",
       "      <td>印地语</td>\n",
       "      <td>159.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>259</th>\n",
       "      <td>追随</td>\n",
       "      <td>1998</td>\n",
       "      <td>8.9</td>\n",
       "      <td>149521.0</td>\n",
       "      <td>克里斯托弗·诺兰</td>\n",
       "      <td>克里斯托弗·诺兰</td>\n",
       "      <td>杰里米·西奥伯德 / 亚历克斯·霍 / 露西·拉塞尔 / 约翰·诺兰 / 迪克·布拉德塞尔 ...</td>\n",
       "      <td>悬疑 / 惊悚 / 犯罪</td>\n",
       "      <td>英国</td>\n",
       "      <td>英语</td>\n",
       "      <td>69.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260</th>\n",
       "      <td>网络谜踪</td>\n",
       "      <td>2018</td>\n",
       "      <td>8.6</td>\n",
       "      <td>430811.0</td>\n",
       "      <td>阿尼什·查甘蒂</td>\n",
       "      <td>阿尼什·查甘蒂 / 赛弗·奥哈尼安</td>\n",
       "      <td>约翰·赵 / 米切尔·拉 / 黛博拉·梅辛 / 约瑟夫·李 / 萨拉·米博·孙 / 亚历克丝...</td>\n",
       "      <td>剧情 / 悬疑 / 惊悚 / 犯罪</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>102.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261</th>\n",
       "      <td>黑鹰坠落</td>\n",
       "      <td>2001</td>\n",
       "      <td>8.7</td>\n",
       "      <td>239402.0</td>\n",
       "      <td>雷德利·斯科特</td>\n",
       "      <td>肯·诺兰 / 马克·鲍登</td>\n",
       "      <td>乔什·哈奈特 / 伊万·麦克格雷格 / 汤姆·塞兹摩尔 / 金·寇兹 / 艾文·布莱纳 / ...</td>\n",
       "      <td>动作 / 历史 / 战争</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>144.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>238 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           片名  上映年份   评分       评价人数        导演                  编剧  \\\n",
       "0      肖申克的救赎  1994  9.7  2317937.0  弗兰克·德拉邦特    弗兰克·德拉邦特 / 斯蒂芬·金   \n",
       "1        霸王别姬  1993  9.6  1720638.0       陈凯歌            芦苇 / 李碧华   \n",
       "2        阿甘正传  1994  9.5  1743966.0  罗伯特·泽米吉斯    艾瑞克·罗斯 / 温斯顿·格鲁姆   \n",
       "3     这个杀手不太冷  1994  9.4  1922740.0     吕克·贝松               吕克·贝松   \n",
       "4       泰坦尼克号  1997  9.4  1706127.0   詹姆斯·卡梅隆             詹姆斯·卡梅隆   \n",
       "..        ...   ...  ...        ...       ...                 ...   \n",
       "256        聚焦  2015  8.8   230899.0    汤姆·麦卡锡      乔希·辛格 / 汤姆·麦卡锡   \n",
       "258  小萝莉的猴神大叔  2015  8.4   404886.0     卡比尔·汗  卡比尔·汗 / 维杰耶德拉·普拉萨德   \n",
       "259        追随  1998  8.9   149521.0  克里斯托弗·诺兰            克里斯托弗·诺兰   \n",
       "260      网络谜踪  2018  8.6   430811.0   阿尼什·查甘蒂   阿尼什·查甘蒂 / 赛弗·奥哈尼安   \n",
       "261      黑鹰坠落  2001  8.7   239402.0   雷德利·斯科特        肯·诺兰 / 马克·鲍登   \n",
       "\n",
       "                                                    主演                 类型  \\\n",
       "0    蒂姆·罗宾斯 / 摩根·弗里曼 / 鲍勃·冈顿 / 威廉姆·赛德勒 / 克兰西·布朗 / 吉...            剧情 / 犯罪   \n",
       "1    张国荣 / 张丰毅 / 巩俐 / 葛优 / 英达 / 蒋雯丽 / 吴大维 / 吕齐 / 雷汉...       剧情 / 爱情 / 同性   \n",
       "2    汤姆·汉克斯 / 罗宾·怀特 / 加里·西尼斯 / 麦凯尔泰·威廉逊 / 莎莉·菲尔德 / ...            剧情 / 爱情   \n",
       "3    让·雷诺 / 娜塔莉·波特曼 / 加里·奥德曼 / 丹尼·爱罗 / 彼得·阿佩尔 / 迈克尔...       剧情 / 动作 / 犯罪   \n",
       "4    莱昂纳多·迪卡普里奥 / 凯特·温丝莱特 / 比利·赞恩 / 凯西·贝茨 / 弗兰西丝·费舍...       剧情 / 爱情 / 灾难   \n",
       "..                                                 ...                ...   \n",
       "256  马克·鲁弗洛 / 迈克尔·基顿 / 瑞秋·麦克亚当斯 / 列维·施瑞博尔 / 约翰·斯拉特里...            剧情 / 传记   \n",
       "258  萨尔曼·汗 / 哈莎莉·马洛特拉 / 卡琳娜·卡普尔 / 纳瓦祖丁·席迪圭 / 欧姆·普瑞 ...       剧情 / 喜剧 / 动作   \n",
       "259  杰里米·西奥伯德 / 亚历克斯·霍 / 露西·拉塞尔 / 约翰·诺兰 / 迪克·布拉德塞尔 ...       悬疑 / 惊悚 / 犯罪   \n",
       "260  约翰·赵 / 米切尔·拉 / 黛博拉·梅辛 / 约瑟夫·李 / 萨拉·米博·孙 / 亚历克丝...  剧情 / 悬疑 / 惊悚 / 犯罪   \n",
       "261  乔什·哈奈特 / 伊万·麦克格雷格 / 汤姆·塞兹摩尔 / 金·寇兹 / 艾文·布莱纳 / ...       动作 / 历史 / 战争   \n",
       "\n",
       "    国家/地区     语言  时长(分钟)  \n",
       "0      美国     英语   142.0  \n",
       "1      中国  汉语普通话   171.0  \n",
       "2      美国     英语   142.0  \n",
       "3      法国    英语    110.0  \n",
       "4      美国    英语    194.0  \n",
       "..    ...    ...     ...  \n",
       "256    美国     英语   128.0  \n",
       "258    印度   印地语    159.0  \n",
       "259    英国     英语    69.0  \n",
       "260    美国     英语   102.0  \n",
       "261    美国    英语    144.0  \n",
       "\n",
       "[238 rows x 11 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dropna()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 13 - 缺失值补全｜整体填充\n",
    "\n",
    "<br>\n",
    "\n",
    "除了删除缺失值最省事之外，将全部缺失值替换为一个 **固定的值/文本** 也是一个较为省事的方法'\n",
    "\n",
    "-> 现在，将全部缺失值替换为 `*`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>上映年份</th>\n",
       "      <th>评分</th>\n",
       "      <th>评价人数</th>\n",
       "      <th>导演</th>\n",
       "      <th>编剧</th>\n",
       "      <th>主演</th>\n",
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       "      <th>国家/地区</th>\n",
       "      <th>语言</th>\n",
       "      <th>时长(分钟)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>肖申克的救赎</td>\n",
       "      <td>1994</td>\n",
       "      <td>9.7</td>\n",
       "      <td>2317937.0</td>\n",
       "      <td>弗兰克·德拉邦特</td>\n",
       "      <td>弗兰克·德拉邦特 / 斯蒂芬·金</td>\n",
       "      <td>蒂姆·罗宾斯 / 摩根·弗里曼 / 鲍勃·冈顿 / 威廉姆·赛德勒 / 克兰西·布朗 / 吉...</td>\n",
       "      <td>剧情 / 犯罪</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>142.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>霸王别姬</td>\n",
       "      <td>1993</td>\n",
       "      <td>9.6</td>\n",
       "      <td>1720638.0</td>\n",
       "      <td>陈凯歌</td>\n",
       "      <td>芦苇 / 李碧华</td>\n",
       "      <td>张国荣 / 张丰毅 / 巩俐 / 葛优 / 英达 / 蒋雯丽 / 吴大维 / 吕齐 / 雷汉...</td>\n",
       "      <td>剧情 / 爱情 / 同性</td>\n",
       "      <td>中国</td>\n",
       "      <td>汉语普通话</td>\n",
       "      <td>171.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>阿甘正传</td>\n",
       "      <td>1994</td>\n",
       "      <td>9.5</td>\n",
       "      <td>1743966.0</td>\n",
       "      <td>罗伯特·泽米吉斯</td>\n",
       "      <td>艾瑞克·罗斯 / 温斯顿·格鲁姆</td>\n",
       "      <td>汤姆·汉克斯 / 罗宾·怀特 / 加里·西尼斯 / 麦凯尔泰·威廉逊 / 莎莉·菲尔德 / ...</td>\n",
       "      <td>剧情 / 爱情</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>142.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>这个杀手不太冷</td>\n",
       "      <td>1994</td>\n",
       "      <td>9.4</td>\n",
       "      <td>1922740.0</td>\n",
       "      <td>吕克·贝松</td>\n",
       "      <td>吕克·贝松</td>\n",
       "      <td>让·雷诺 / 娜塔莉·波特曼 / 加里·奥德曼 / 丹尼·爱罗 / 彼得·阿佩尔 / 迈克尔...</td>\n",
       "      <td>剧情 / 动作 / 犯罪</td>\n",
       "      <td>法国</td>\n",
       "      <td>英语</td>\n",
       "      <td>110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>泰坦尼克号</td>\n",
       "      <td>1997</td>\n",
       "      <td>9.4</td>\n",
       "      <td>1706127.0</td>\n",
       "      <td>詹姆斯·卡梅隆</td>\n",
       "      <td>詹姆斯·卡梅隆</td>\n",
       "      <td>莱昂纳多·迪卡普里奥 / 凯特·温丝莱特 / 比利·赞恩 / 凯西·贝茨 / 弗兰西丝·费舍...</td>\n",
       "      <td>剧情 / 爱情 / 灾难</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>194.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>257</th>\n",
       "      <td>浪潮</td>\n",
       "      <td>2008</td>\n",
       "      <td>8.7</td>\n",
       "      <td>223511.0</td>\n",
       "      <td>丹尼斯·甘塞尔</td>\n",
       "      <td>丹尼斯·甘塞尔 / 彼得·图万斯 / 约翰尼·道金斯 / 罗恩·比恩巴赫 / 罗恩·琼斯</td>\n",
       "      <td>于尔根·福格尔 / 弗雷德里克·劳 / 马克思·雷迈特 / 詹妮弗·乌尔里希 / 克里斯蒂安...</td>\n",
       "      <td>剧情 / 惊悚</td>\n",
       "      <td>*</td>\n",
       "      <td>德语</td>\n",
       "      <td>107.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>258</th>\n",
       "      <td>小萝莉的猴神大叔</td>\n",
       "      <td>2015</td>\n",
       "      <td>8.4</td>\n",
       "      <td>404886.0</td>\n",
       "      <td>卡比尔·汗</td>\n",
       "      <td>卡比尔·汗 / 维杰耶德拉·普拉萨德</td>\n",
       "      <td>萨尔曼·汗 / 哈莎莉·马洛特拉 / 卡琳娜·卡普尔 / 纳瓦祖丁·席迪圭 / 欧姆·普瑞 ...</td>\n",
       "      <td>剧情 / 喜剧 / 动作</td>\n",
       "      <td>印度</td>\n",
       "      <td>印地语</td>\n",
       "      <td>159.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>259</th>\n",
       "      <td>追随</td>\n",
       "      <td>1998</td>\n",
       "      <td>8.9</td>\n",
       "      <td>149521.0</td>\n",
       "      <td>克里斯托弗·诺兰</td>\n",
       "      <td>克里斯托弗·诺兰</td>\n",
       "      <td>杰里米·西奥伯德 / 亚历克斯·霍 / 露西·拉塞尔 / 约翰·诺兰 / 迪克·布拉德塞尔 ...</td>\n",
       "      <td>悬疑 / 惊悚 / 犯罪</td>\n",
       "      <td>英国</td>\n",
       "      <td>英语</td>\n",
       "      <td>69.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260</th>\n",
       "      <td>网络谜踪</td>\n",
       "      <td>2018</td>\n",
       "      <td>8.6</td>\n",
       "      <td>430811.0</td>\n",
       "      <td>阿尼什·查甘蒂</td>\n",
       "      <td>阿尼什·查甘蒂 / 赛弗·奥哈尼安</td>\n",
       "      <td>约翰·赵 / 米切尔·拉 / 黛博拉·梅辛 / 约瑟夫·李 / 萨拉·米博·孙 / 亚历克丝...</td>\n",
       "      <td>剧情 / 悬疑 / 惊悚 / 犯罪</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>102.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261</th>\n",
       "      <td>黑鹰坠落</td>\n",
       "      <td>2001</td>\n",
       "      <td>8.7</td>\n",
       "      <td>239402.0</td>\n",
       "      <td>雷德利·斯科特</td>\n",
       "      <td>肯·诺兰 / 马克·鲍登</td>\n",
       "      <td>乔什·哈奈特 / 伊万·麦克格雷格 / 汤姆·塞兹摩尔 / 金·寇兹 / 艾文·布莱纳 / ...</td>\n",
       "      <td>动作 / 历史 / 战争</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>144.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>262 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           片名  上映年份   评分       评价人数        导演  \\\n",
       "0      肖申克的救赎  1994  9.7  2317937.0  弗兰克·德拉邦特   \n",
       "1        霸王别姬  1993  9.6  1720638.0       陈凯歌   \n",
       "2        阿甘正传  1994  9.5  1743966.0  罗伯特·泽米吉斯   \n",
       "3     这个杀手不太冷  1994  9.4  1922740.0     吕克·贝松   \n",
       "4       泰坦尼克号  1997  9.4  1706127.0   詹姆斯·卡梅隆   \n",
       "..        ...   ...  ...        ...       ...   \n",
       "257        浪潮  2008  8.7   223511.0   丹尼斯·甘塞尔   \n",
       "258  小萝莉的猴神大叔  2015  8.4   404886.0     卡比尔·汗   \n",
       "259        追随  1998  8.9   149521.0  克里斯托弗·诺兰   \n",
       "260      网络谜踪  2018  8.6   430811.0   阿尼什·查甘蒂   \n",
       "261      黑鹰坠落  2001  8.7   239402.0   雷德利·斯科特   \n",
       "\n",
       "                                               编剧  \\\n",
       "0                                弗兰克·德拉邦特 / 斯蒂芬·金   \n",
       "1                                        芦苇 / 李碧华   \n",
       "2                                艾瑞克·罗斯 / 温斯顿·格鲁姆   \n",
       "3                                           吕克·贝松   \n",
       "4                                         詹姆斯·卡梅隆   \n",
       "..                                            ...   \n",
       "257  丹尼斯·甘塞尔 / 彼得·图万斯 / 约翰尼·道金斯 / 罗恩·比恩巴赫 / 罗恩·琼斯   \n",
       "258                            卡比尔·汗 / 维杰耶德拉·普拉萨德   \n",
       "259                                      克里斯托弗·诺兰   \n",
       "260                             阿尼什·查甘蒂 / 赛弗·奥哈尼安   \n",
       "261                                  肯·诺兰 / 马克·鲍登   \n",
       "\n",
       "                                                    主演                 类型  \\\n",
       "0    蒂姆·罗宾斯 / 摩根·弗里曼 / 鲍勃·冈顿 / 威廉姆·赛德勒 / 克兰西·布朗 / 吉...            剧情 / 犯罪   \n",
       "1    张国荣 / 张丰毅 / 巩俐 / 葛优 / 英达 / 蒋雯丽 / 吴大维 / 吕齐 / 雷汉...       剧情 / 爱情 / 同性   \n",
       "2    汤姆·汉克斯 / 罗宾·怀特 / 加里·西尼斯 / 麦凯尔泰·威廉逊 / 莎莉·菲尔德 / ...            剧情 / 爱情   \n",
       "3    让·雷诺 / 娜塔莉·波特曼 / 加里·奥德曼 / 丹尼·爱罗 / 彼得·阿佩尔 / 迈克尔...       剧情 / 动作 / 犯罪   \n",
       "4    莱昂纳多·迪卡普里奥 / 凯特·温丝莱特 / 比利·赞恩 / 凯西·贝茨 / 弗兰西丝·费舍...       剧情 / 爱情 / 灾难   \n",
       "..                                                 ...                ...   \n",
       "257  于尔根·福格尔 / 弗雷德里克·劳 / 马克思·雷迈特 / 詹妮弗·乌尔里希 / 克里斯蒂安...            剧情 / 惊悚   \n",
       "258  萨尔曼·汗 / 哈莎莉·马洛特拉 / 卡琳娜·卡普尔 / 纳瓦祖丁·席迪圭 / 欧姆·普瑞 ...       剧情 / 喜剧 / 动作   \n",
       "259  杰里米·西奥伯德 / 亚历克斯·霍 / 露西·拉塞尔 / 约翰·诺兰 / 迪克·布拉德塞尔 ...       悬疑 / 惊悚 / 犯罪   \n",
       "260  约翰·赵 / 米切尔·拉 / 黛博拉·梅辛 / 约瑟夫·李 / 萨拉·米博·孙 / 亚历克丝...  剧情 / 悬疑 / 惊悚 / 犯罪   \n",
       "261  乔什·哈奈特 / 伊万·麦克格雷格 / 汤姆·塞兹摩尔 / 金·寇兹 / 艾文·布莱纳 / ...       动作 / 历史 / 战争   \n",
       "\n",
       "    国家/地区     语言 时长(分钟)  \n",
       "0      美国     英语  142.0  \n",
       "1      中国  汉语普通话  171.0  \n",
       "2      美国     英语  142.0  \n",
       "3      法国    英语   110.0  \n",
       "4      美国    英语   194.0  \n",
       "..    ...    ...    ...  \n",
       "257     *     德语  107.0  \n",
       "258    印度   印地语   159.0  \n",
       "259    英国     英语   69.0  \n",
       "260    美国     英语  102.0  \n",
       "261    美国    英语   144.0  \n",
       "\n",
       "[262 rows x 11 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.fillna(\"*\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 14 - 缺失值补全｜向上填充"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从上一小节的查看数据中，不难发现整理数据是按照评分进行降序排列的\n",
    "\n",
    "因此对于评分列的缺失值处理，我们可以用上一个电影的评分进行填充\n",
    "\n",
    "-> 现在将评分列的缺失值，替换为上一个电影的评分"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# df[df.评分.isna()].评分 = df[df[df.评分.isna()].index -1].评分\n",
    "\n",
    "df.loc[df.评分.isna(), \"评分\"] = df.loc[df[df.评分.isna()].index -1 ].评分.values\n",
    "\n",
    "#df.loc[df[df.评分.isna()].index -1 ].评分"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 15 - 缺失值补全｜整体均值填充"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "对于评价人数列的缺失值处理，我们可以使用整列的均值进行填充\n",
    "\n",
    "-> 现在，将评价人数列的缺失值，用整列的均值进行填充"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# int(df.评价人数.mean())\n",
    "df.loc[df.评价人数.isna(), '评价人数'] = int(df.评价人数.mean())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 16 - 缺失值补全｜上下均值填充\n",
    "\n",
    "<br>\n",
    "\n",
    "除了可以使用整列的均值进行填充，也可以使用缺失值位置的上下均值进行填充、\n",
    "\n",
    "-> 现在，将评价人数列的缺失值，用上下数字的均值进行填充"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.loc[df.评价人数.isna(), '评价人数'] = (df.loc[df[df.评价人数.isna()].index - 1].评价人数.values + df.loc[df[df.评价人数.isna()].index + 1].评价人数.values) / 2\n",
    "\n",
    "# df.loc[[18,19,20,134,135,136,165,166,167]]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 17 -缺失值补全｜匹配填充\n",
    "\n",
    "<br>\n",
    "\n",
    "除了利用均值填充，有时还需要根据另一列的值进行匹配填充\n",
    "\n",
    "-> 现在填充 “语言” 列的缺失值，要求根据 “国家/地区” 列的值进行填充\n",
    "\n",
    "> 例如 《海上钢琴师》国家/地区为 意大利，根据其他意大利国家对应的语言来看，应填充为 意大利语\n",
    "\n",
    "**注意：此题会有多种解法**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in df.index:\n",
    "    if pd.isna(df.loc[i, '语言']):\n",
    "        area = df.loc[i, '国家/地区']\n",
    "        if (area == '美国'):\n",
    "            df.loc[i, '语言'] = '英语'\n",
    "        else:\n",
    "            df.loc[i, '语言'] = area + \"语\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 重复值处理"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 18 - 查找重复值\n",
    "\n",
    "<br>\n",
    "\n",
    "将全部重复值所在的行筛选出来\n",
    "\n",
    "**注意：此题会有多种解法**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>片名</th>\n",
       "      <th>上映年份</th>\n",
       "      <th>评分</th>\n",
       "      <th>评价人数</th>\n",
       "      <th>导演</th>\n",
       "      <th>编剧</th>\n",
       "      <th>主演</th>\n",
       "      <th>类型</th>\n",
       "      <th>国家/地区</th>\n",
       "      <th>语言</th>\n",
       "      <th>时长(分钟)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>人生果实</td>\n",
       "      <td>2017</td>\n",
       "      <td>9.5</td>\n",
       "      <td>132229.0</td>\n",
       "      <td>伏原健之</td>\n",
       "      <td>津端修一 / 津端英子 / 树木希林</td>\n",
       "      <td>纪录片</td>\n",
       "      <td>life-is-fruity.com</td>\n",
       "      <td>日本</td>\n",
       "      <td>日语</td>\n",
       "      <td>91.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>人生果实</td>\n",
       "      <td>2017</td>\n",
       "      <td>9.5</td>\n",
       "      <td>132229.0</td>\n",
       "      <td>伏原健之</td>\n",
       "      <td>津端修一 / 津端英子 / 树木希林</td>\n",
       "      <td>纪录片</td>\n",
       "      <td>life-is-fruity.com</td>\n",
       "      <td>日本</td>\n",
       "      <td>日语</td>\n",
       "      <td>91.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>侧耳倾听</td>\n",
       "      <td>1995</td>\n",
       "      <td>8.9</td>\n",
       "      <td>371774.0</td>\n",
       "      <td>近藤喜文</td>\n",
       "      <td>宫崎骏 / 柊葵</td>\n",
       "      <td>本名阳子 / 小林桂树 / 高山南 / 高桥一生 / 山下容莉枝 / 室井滋 / 露口茂 /...</td>\n",
       "      <td>剧情 / 爱情 / 动画</td>\n",
       "      <td>日本</td>\n",
       "      <td>日语</td>\n",
       "      <td>111.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>侧耳倾听</td>\n",
       "      <td>1995</td>\n",
       "      <td>8.9</td>\n",
       "      <td>371774.0</td>\n",
       "      <td>近藤喜文</td>\n",
       "      <td>宫崎骏 / 柊葵</td>\n",
       "      <td>本名阳子 / 小林桂树 / 高山南 / 高桥一生 / 山下容莉枝 / 室井滋 / 露口茂 /...</td>\n",
       "      <td>剧情 / 爱情 / 动画</td>\n",
       "      <td>日本</td>\n",
       "      <td>日语</td>\n",
       "      <td>111.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>倩女幽魂</td>\n",
       "      <td>1987</td>\n",
       "      <td>8.7</td>\n",
       "      <td>591835.0</td>\n",
       "      <td>程小东</td>\n",
       "      <td>阮继志</td>\n",
       "      <td>张国荣 / 王祖贤 / 午马 / 刘兆铭 / 林威 / 薛芷伦 / 胡大为 / 王晶</td>\n",
       "      <td>爱情 / 奇幻 / 武侠 / 古装</td>\n",
       "      <td>中国</td>\n",
       "      <td>粤语</td>\n",
       "      <td>98.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>倩女幽魂</td>\n",
       "      <td>1987</td>\n",
       "      <td>8.7</td>\n",
       "      <td>591835.0</td>\n",
       "      <td>程小东</td>\n",
       "      <td>阮继志</td>\n",
       "      <td>张国荣 / 王祖贤 / 午马 / 刘兆铭 / 林威 / 薛芷伦 / 胡大为 / 王晶</td>\n",
       "      <td>爱情 / 奇幻 / 武侠 / 古装</td>\n",
       "      <td>中国</td>\n",
       "      <td>粤语</td>\n",
       "      <td>98.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>无人知晓</td>\n",
       "      <td>2004</td>\n",
       "      <td>9.1</td>\n",
       "      <td>233881.0</td>\n",
       "      <td>是枝裕和</td>\n",
       "      <td>是枝裕和</td>\n",
       "      <td>柳乐优弥 / 北浦爱 / 木村飞影 / 清水萌萌子 / 韩英惠 / 江原由希子 / 串田和美...</td>\n",
       "      <td>剧情</td>\n",
       "      <td>日本</td>\n",
       "      <td>日语</td>\n",
       "      <td>141.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>无人知晓</td>\n",
       "      <td>2004</td>\n",
       "      <td>9.1</td>\n",
       "      <td>233881.0</td>\n",
       "      <td>是枝裕和</td>\n",
       "      <td>是枝裕和</td>\n",
       "      <td>柳乐优弥 / 北浦爱 / 木村飞影 / 清水萌萌子 / 韩英惠 / 江原由希子 / 串田和美...</td>\n",
       "      <td>剧情</td>\n",
       "      <td>日本</td>\n",
       "      <td>日语</td>\n",
       "      <td>141.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>无人知晓</td>\n",
       "      <td>2004</td>\n",
       "      <td>9.1</td>\n",
       "      <td>233881.0</td>\n",
       "      <td>是枝裕和</td>\n",
       "      <td>是枝裕和</td>\n",
       "      <td>柳乐优弥 / 北浦爱 / 木村飞影 / 清水萌萌子 / 韩英惠 / 江原由希子 / 串田和美...</td>\n",
       "      <td>剧情</td>\n",
       "      <td>日本</td>\n",
       "      <td>日语</td>\n",
       "      <td>141.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>无人知晓</td>\n",
       "      <td>2004</td>\n",
       "      <td>9.1</td>\n",
       "      <td>233881.0</td>\n",
       "      <td>是枝裕和</td>\n",
       "      <td>是枝裕和</td>\n",
       "      <td>柳乐优弥 / 北浦爱 / 木村飞影 / 清水萌萌子 / 韩英惠 / 江原由希子 / 串田和美...</td>\n",
       "      <td>剧情</td>\n",
       "      <td>日本</td>\n",
       "      <td>日语</td>\n",
       "      <td>141.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>菊次郎的夏天</td>\n",
       "      <td>1999</td>\n",
       "      <td>8.8</td>\n",
       "      <td>457770.0</td>\n",
       "      <td>北野武</td>\n",
       "      <td>北野武</td>\n",
       "      <td>北野武 / 关口雄介 / 岸本加世子 / 吉行和子 / 细川典江 / 大家由祐子 / 磨赤儿...</td>\n",
       "      <td>剧情 / 喜剧</td>\n",
       "      <td>日本</td>\n",
       "      <td>日语</td>\n",
       "      <td>121.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>菊次郎的夏天</td>\n",
       "      <td>1999</td>\n",
       "      <td>8.8</td>\n",
       "      <td>457770.0</td>\n",
       "      <td>北野武</td>\n",
       "      <td>北野武</td>\n",
       "      <td>北野武 / 关口雄介 / 岸本加世子 / 吉行和子 / 细川典江 / 大家由祐子 / 磨赤儿...</td>\n",
       "      <td>剧情 / 喜剧</td>\n",
       "      <td>日本</td>\n",
       "      <td>日语</td>\n",
       "      <td>121.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>超能陆战队</td>\n",
       "      <td>2014</td>\n",
       "      <td>8.7</td>\n",
       "      <td>810643.0</td>\n",
       "      <td>唐·霍尔 / 克里斯·威廉姆斯</td>\n",
       "      <td>乔丹·罗伯茨 / 丹尼尔·吉尔森 / 罗伯特·L·贝尔德</td>\n",
       "      <td>斯科特·安第斯 / 瑞恩·波特 / 丹尼尔·海尼 / T·J·米勒 / 杰米·钟 / 小达蒙...</td>\n",
       "      <td>喜剧 / 动作 / 科幻 / 动画 / 冒险</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>102.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>超能陆战队</td>\n",
       "      <td>2014</td>\n",
       "      <td>8.7</td>\n",
       "      <td>810643.0</td>\n",
       "      <td>唐·霍尔 / 克里斯·威廉姆斯</td>\n",
       "      <td>乔丹·罗伯茨 / 丹尼尔·吉尔森 / 罗伯特·L·贝尔德</td>\n",
       "      <td>斯科特·安第斯 / 瑞恩·波特 / 丹尼尔·海尼 / T·J·米勒 / 杰米·钟 / 小达蒙...</td>\n",
       "      <td>喜剧 / 动作 / 科幻 / 动画 / 冒险</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>102.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>超脱</td>\n",
       "      <td>2011</td>\n",
       "      <td>8.9</td>\n",
       "      <td>392204.0</td>\n",
       "      <td>托尼·凯耶</td>\n",
       "      <td>卡尔·隆德</td>\n",
       "      <td>艾德里安·布洛迪 / 马西娅·盖伊·哈登 / 詹姆斯·肯恩 / 克里斯蒂娜·亨德里克斯 / ...</td>\n",
       "      <td>剧情</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>超脱</td>\n",
       "      <td>2011</td>\n",
       "      <td>8.9</td>\n",
       "      <td>392204.0</td>\n",
       "      <td>托尼·凯耶</td>\n",
       "      <td>卡尔·隆德</td>\n",
       "      <td>艾德里安·布洛迪 / 马西娅·盖伊·哈登 / 詹姆斯·肯恩 / 克里斯蒂娜·亨德里克斯 / ...</td>\n",
       "      <td>剧情</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>重庆森林</td>\n",
       "      <td>1994</td>\n",
       "      <td>8.8</td>\n",
       "      <td>639120.0</td>\n",
       "      <td>王家卫</td>\n",
       "      <td>王家卫</td>\n",
       "      <td>林青霞 / 金城武 / 梁朝伟 / 王菲 / 周嘉玲</td>\n",
       "      <td>剧情 / 爱情</td>\n",
       "      <td>中国</td>\n",
       "      <td>粤语</td>\n",
       "      <td>102.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>重庆森林</td>\n",
       "      <td>1994</td>\n",
       "      <td>8.8</td>\n",
       "      <td>639120.0</td>\n",
       "      <td>王家卫</td>\n",
       "      <td>王家卫</td>\n",
       "      <td>林青霞 / 金城武 / 梁朝伟 / 王菲 / 周嘉玲</td>\n",
       "      <td>剧情 / 爱情</td>\n",
       "      <td>中国</td>\n",
       "      <td>粤语</td>\n",
       "      <td>102.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         片名  上映年份   评分      评价人数               导演  \\\n",
       "100    人生果实  2017  9.5  132229.0             伏原健之   \n",
       "128    人生果实  2017  9.5  132229.0             伏原健之   \n",
       "101    侧耳倾听  1995  8.9  371774.0             近藤喜文   \n",
       "129    侧耳倾听  1995  8.9  371774.0             近藤喜文   \n",
       "132    倩女幽魂  1987  8.7  591835.0              程小东   \n",
       "104    倩女幽魂  1987  8.7  591835.0              程小东   \n",
       "130    无人知晓  2004  9.1  233881.0             是枝裕和   \n",
       "112    无人知晓  2004  9.1  233881.0             是枝裕和   \n",
       "102    无人知晓  2004  9.1  233881.0             是枝裕和   \n",
       "111    无人知晓  2004  9.1  233881.0             是枝裕和   \n",
       "127  菊次郎的夏天  1999  8.8  457770.0              北野武   \n",
       "99   菊次郎的夏天  1999  8.8  457770.0              北野武   \n",
       "131   超能陆战队  2014  8.7  810643.0  唐·霍尔 / 克里斯·威廉姆斯   \n",
       "103   超能陆战队  2014  8.7  810643.0  唐·霍尔 / 克里斯·威廉姆斯   \n",
       "119      超脱  2011  8.9  392204.0            托尼·凯耶   \n",
       "94       超脱  2011  8.9  392204.0            托尼·凯耶   \n",
       "116    重庆森林  1994  8.8  639120.0              王家卫   \n",
       "117    重庆森林  1994  8.8  639120.0              王家卫   \n",
       "\n",
       "                               编剧  \\\n",
       "100            津端修一 / 津端英子 / 树木希林   \n",
       "128            津端修一 / 津端英子 / 树木希林   \n",
       "101                      宫崎骏 / 柊葵   \n",
       "129                      宫崎骏 / 柊葵   \n",
       "132                           阮继志   \n",
       "104                           阮继志   \n",
       "130                          是枝裕和   \n",
       "112                          是枝裕和   \n",
       "102                          是枝裕和   \n",
       "111                          是枝裕和   \n",
       "127                           北野武   \n",
       "99                            北野武   \n",
       "131  乔丹·罗伯茨 / 丹尼尔·吉尔森 / 罗伯特·L·贝尔德   \n",
       "103  乔丹·罗伯茨 / 丹尼尔·吉尔森 / 罗伯特·L·贝尔德   \n",
       "119                         卡尔·隆德   \n",
       "94                          卡尔·隆德   \n",
       "116                           王家卫   \n",
       "117                           王家卫   \n",
       "\n",
       "                                                    主演  \\\n",
       "100                                                纪录片   \n",
       "128                                                纪录片   \n",
       "101  本名阳子 / 小林桂树 / 高山南 / 高桥一生 / 山下容莉枝 / 室井滋 / 露口茂 /...   \n",
       "129  本名阳子 / 小林桂树 / 高山南 / 高桥一生 / 山下容莉枝 / 室井滋 / 露口茂 /...   \n",
       "132         张国荣 / 王祖贤 / 午马 / 刘兆铭 / 林威 / 薛芷伦 / 胡大为 / 王晶   \n",
       "104         张国荣 / 王祖贤 / 午马 / 刘兆铭 / 林威 / 薛芷伦 / 胡大为 / 王晶   \n",
       "130  柳乐优弥 / 北浦爱 / 木村飞影 / 清水萌萌子 / 韩英惠 / 江原由希子 / 串田和美...   \n",
       "112  柳乐优弥 / 北浦爱 / 木村飞影 / 清水萌萌子 / 韩英惠 / 江原由希子 / 串田和美...   \n",
       "102  柳乐优弥 / 北浦爱 / 木村飞影 / 清水萌萌子 / 韩英惠 / 江原由希子 / 串田和美...   \n",
       "111  柳乐优弥 / 北浦爱 / 木村飞影 / 清水萌萌子 / 韩英惠 / 江原由希子 / 串田和美...   \n",
       "127  北野武 / 关口雄介 / 岸本加世子 / 吉行和子 / 细川典江 / 大家由祐子 / 磨赤儿...   \n",
       "99   北野武 / 关口雄介 / 岸本加世子 / 吉行和子 / 细川典江 / 大家由祐子 / 磨赤儿...   \n",
       "131  斯科特·安第斯 / 瑞恩·波特 / 丹尼尔·海尼 / T·J·米勒 / 杰米·钟 / 小达蒙...   \n",
       "103  斯科特·安第斯 / 瑞恩·波特 / 丹尼尔·海尼 / T·J·米勒 / 杰米·钟 / 小达蒙...   \n",
       "119  艾德里安·布洛迪 / 马西娅·盖伊·哈登 / 詹姆斯·肯恩 / 克里斯蒂娜·亨德里克斯 / ...   \n",
       "94   艾德里安·布洛迪 / 马西娅·盖伊·哈登 / 詹姆斯·肯恩 / 克里斯蒂娜·亨德里克斯 / ...   \n",
       "116                         林青霞 / 金城武 / 梁朝伟 / 王菲 / 周嘉玲   \n",
       "117                         林青霞 / 金城武 / 梁朝伟 / 王菲 / 周嘉玲   \n",
       "\n",
       "                         类型 国家/地区   语言  时长(分钟)  \n",
       "100      life-is-fruity.com    日本   日语    91.0  \n",
       "128      life-is-fruity.com    日本   日语    91.0  \n",
       "101            剧情 / 爱情 / 动画    日本  日语    111.0  \n",
       "129            剧情 / 爱情 / 动画    日本  日语    111.0  \n",
       "132       爱情 / 奇幻 / 武侠 / 古装    中国   粤语    98.0  \n",
       "104       爱情 / 奇幻 / 武侠 / 古装    中国   粤语    98.0  \n",
       "130                      剧情    日本   日语   141.0  \n",
       "112                      剧情    日本   日语   141.0  \n",
       "102                      剧情    日本   日语   141.0  \n",
       "111                      剧情    日本   日语   141.0  \n",
       "127                 剧情 / 喜剧    日本   日语   121.0  \n",
       "99                  剧情 / 喜剧    日本   日语   121.0  \n",
       "131  喜剧 / 动作 / 科幻 / 动画 / 冒险    美国   英语   102.0  \n",
       "103  喜剧 / 动作 / 科幻 / 动画 / 冒险    美国   英语   102.0  \n",
       "119                      剧情    美国   英语    97.0  \n",
       "94                       剧情    美国   英语    97.0  \n",
       "116                 剧情 / 爱情    中国  粤语    102.0  \n",
       "117                 剧情 / 爱情    中国  粤语    102.0  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# df['片名'].value_counts() > 1\n",
    "df[df.duplicated(keep=False)].sort_values('片名')\n",
    "#df[df.duplicated(keep=False)].groupby('片名').size().sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 19 -查找重复值｜指定\n",
    "\n",
    "上面是所有列完全重复的情况，但有时我们只需要根据某列查找重复值\n",
    "\n",
    "-> 查找 片名 列全部重复值\n",
    "\n",
    "**注意：此题会有多种解法**\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>片名</th>\n",
       "      <th>上映年份</th>\n",
       "      <th>评分</th>\n",
       "      <th>评价人数</th>\n",
       "      <th>导演</th>\n",
       "      <th>编剧</th>\n",
       "      <th>主演</th>\n",
       "      <th>类型</th>\n",
       "      <th>国家/地区</th>\n",
       "      <th>语言</th>\n",
       "      <th>时长(分钟)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>人生果实</td>\n",
       "      <td>2017</td>\n",
       "      <td>9.5</td>\n",
       "      <td>132229.0</td>\n",
       "      <td>伏原健之</td>\n",
       "      <td>津端修一 / 津端英子 / 树木希林</td>\n",
       "      <td>纪录片</td>\n",
       "      <td>life-is-fruity.com</td>\n",
       "      <td>日本</td>\n",
       "      <td>日语</td>\n",
       "      <td>91.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>人生果实</td>\n",
       "      <td>2017</td>\n",
       "      <td>9.5</td>\n",
       "      <td>132229.0</td>\n",
       "      <td>伏原健之</td>\n",
       "      <td>津端修一 / 津端英子 / 树木希林</td>\n",
       "      <td>纪录片</td>\n",
       "      <td>life-is-fruity.com</td>\n",
       "      <td>日本</td>\n",
       "      <td>日语</td>\n",
       "      <td>91.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>侧耳倾听</td>\n",
       "      <td>1995</td>\n",
       "      <td>8.9</td>\n",
       "      <td>371774.0</td>\n",
       "      <td>近藤喜文</td>\n",
       "      <td>宫崎骏 / 柊葵</td>\n",
       "      <td>本名阳子 / 小林桂树 / 高山南 / 高桥一生 / 山下容莉枝 / 室井滋 / 露口茂 /...</td>\n",
       "      <td>剧情 / 爱情 / 动画</td>\n",
       "      <td>日本</td>\n",
       "      <td>日语</td>\n",
       "      <td>111.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>侧耳倾听</td>\n",
       "      <td>1995</td>\n",
       "      <td>8.9</td>\n",
       "      <td>371774.0</td>\n",
       "      <td>近藤喜文</td>\n",
       "      <td>宫崎骏 / 柊葵</td>\n",
       "      <td>本名阳子 / 小林桂树 / 高山南 / 高桥一生 / 山下容莉枝 / 室井滋 / 露口茂 /...</td>\n",
       "      <td>剧情 / 爱情 / 动画</td>\n",
       "      <td>日本</td>\n",
       "      <td>日语</td>\n",
       "      <td>111.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>倩女幽魂</td>\n",
       "      <td>1987</td>\n",
       "      <td>8.7</td>\n",
       "      <td>591835.0</td>\n",
       "      <td>程小东</td>\n",
       "      <td>阮继志</td>\n",
       "      <td>张国荣 / 王祖贤 / 午马 / 刘兆铭 / 林威 / 薛芷伦 / 胡大为 / 王晶</td>\n",
       "      <td>爱情 / 奇幻 / 武侠 / 古装</td>\n",
       "      <td>中国</td>\n",
       "      <td>粤语</td>\n",
       "      <td>98.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>倩女幽魂</td>\n",
       "      <td>1987</td>\n",
       "      <td>8.7</td>\n",
       "      <td>591835.0</td>\n",
       "      <td>程小东</td>\n",
       "      <td>阮继志</td>\n",
       "      <td>张国荣 / 王祖贤 / 午马 / 刘兆铭 / 林威 / 薛芷伦 / 胡大为 / 王晶</td>\n",
       "      <td>爱情 / 奇幻 / 武侠 / 古装</td>\n",
       "      <td>中国</td>\n",
       "      <td>粤语</td>\n",
       "      <td>98.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>小森林</td>\n",
       "      <td>2014</td>\n",
       "      <td>9.0</td>\n",
       "      <td>341623.0</td>\n",
       "      <td>森淳一</td>\n",
       "      <td>森淳一 / 五十岚大介</td>\n",
       "      <td>桥本爱 / 三浦贵大 / 松冈茉优 / 温水洋一 / 桐岛加恋</td>\n",
       "      <td>剧情</td>\n",
       "      <td>日本</td>\n",
       "      <td>日语</td>\n",
       "      <td>111.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>小森林</td>\n",
       "      <td>2015</td>\n",
       "      <td>9.0</td>\n",
       "      <td>306686.0</td>\n",
       "      <td>森淳一</td>\n",
       "      <td>森淳一 / 五十岚大介</td>\n",
       "      <td>桥本爱 / 三浦贵大 / 松冈茉优 / 温水洋一 / 桐岛加恋</td>\n",
       "      <td>剧情</td>\n",
       "      <td>日本</td>\n",
       "      <td>日语</td>\n",
       "      <td>120.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>无人知晓</td>\n",
       "      <td>2004</td>\n",
       "      <td>9.1</td>\n",
       "      <td>233881.0</td>\n",
       "      <td>是枝裕和</td>\n",
       "      <td>是枝裕和</td>\n",
       "      <td>柳乐优弥 / 北浦爱 / 木村飞影 / 清水萌萌子 / 韩英惠 / 江原由希子 / 串田和美...</td>\n",
       "      <td>剧情</td>\n",
       "      <td>日本</td>\n",
       "      <td>日语</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>无人知晓</td>\n",
       "      <td>2004</td>\n",
       "      <td>9.1</td>\n",
       "      <td>233881.0</td>\n",
       "      <td>是枝裕和</td>\n",
       "      <td>是枝裕和</td>\n",
       "      <td>柳乐优弥 / 北浦爱 / 木村飞影 / 清水萌萌子 / 韩英惠 / 江原由希子 / 串田和美...</td>\n",
       "      <td>剧情</td>\n",
       "      <td>日本</td>\n",
       "      <td>日语</td>\n",
       "      <td>141.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>无人知晓</td>\n",
       "      <td>2004</td>\n",
       "      <td>9.1</td>\n",
       "      <td>233881.0</td>\n",
       "      <td>是枝裕和</td>\n",
       "      <td>是枝裕和</td>\n",
       "      <td>柳乐优弥 / 北浦爱 / 木村飞影 / 清水萌萌子 / 韩英惠 / 江原由希子 / 串田和美...</td>\n",
       "      <td>剧情</td>\n",
       "      <td>日本</td>\n",
       "      <td>日语</td>\n",
       "      <td>141.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>无人知晓</td>\n",
       "      <td>2004</td>\n",
       "      <td>9.1</td>\n",
       "      <td>233881.0</td>\n",
       "      <td>是枝裕和</td>\n",
       "      <td>是枝裕和</td>\n",
       "      <td>柳乐优弥 / 北浦爱 / 木村飞影 / 清水萌萌子 / 韩英惠 / 江原由希子 / 串田和美...</td>\n",
       "      <td>剧情</td>\n",
       "      <td>日本</td>\n",
       "      <td>日语</td>\n",
       "      <td>141.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>无人知晓</td>\n",
       "      <td>2004</td>\n",
       "      <td>9.1</td>\n",
       "      <td>233881.0</td>\n",
       "      <td>是枝裕和</td>\n",
       "      <td>是枝裕和</td>\n",
       "      <td>柳乐优弥 / 北浦爱 / 木村飞影 / 清水萌萌子 / 韩英惠 / 江原由希子 / 串田和美...</td>\n",
       "      <td>剧情</td>\n",
       "      <td>日本</td>\n",
       "      <td>日语</td>\n",
       "      <td>141.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>甜蜜蜜</td>\n",
       "      <td>1996</td>\n",
       "      <td>NaN</td>\n",
       "      <td>420172.0</td>\n",
       "      <td>陈可辛</td>\n",
       "      <td>岸西</td>\n",
       "      <td>黎明 / 张曼玉 / 杨恭如 / 曾志伟 / 杜可风 / 张同祖 / 诸慧荷 / 丁羽</td>\n",
       "      <td>剧情 / 爱情</td>\n",
       "      <td>中国</td>\n",
       "      <td>粤语</td>\n",
       "      <td>118.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>甜蜜蜜</td>\n",
       "      <td>1996</td>\n",
       "      <td>8.9</td>\n",
       "      <td>420172.0</td>\n",
       "      <td>陈可辛</td>\n",
       "      <td>岸西</td>\n",
       "      <td>黎明 / 张曼玉 / 杨恭如 / 曾志伟 / 杜可风 / 张同祖 / 诸慧荷 / 丁羽</td>\n",
       "      <td>剧情 / 爱情</td>\n",
       "      <td>中国</td>\n",
       "      <td>粤语</td>\n",
       "      <td>118.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>菊次郎的夏天</td>\n",
       "      <td>1999</td>\n",
       "      <td>8.8</td>\n",
       "      <td>457770.0</td>\n",
       "      <td>北野武</td>\n",
       "      <td>北野武</td>\n",
       "      <td>北野武 / 关口雄介 / 岸本加世子 / 吉行和子 / 细川典江 / 大家由祐子 / 磨赤儿...</td>\n",
       "      <td>剧情 / 喜剧</td>\n",
       "      <td>日本</td>\n",
       "      <td>日语</td>\n",
       "      <td>121.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>菊次郎的夏天</td>\n",
       "      <td>1999</td>\n",
       "      <td>8.8</td>\n",
       "      <td>457770.0</td>\n",
       "      <td>北野武</td>\n",
       "      <td>北野武</td>\n",
       "      <td>北野武 / 关口雄介 / 岸本加世子 / 吉行和子 / 细川典江 / 大家由祐子 / 磨赤儿...</td>\n",
       "      <td>剧情 / 喜剧</td>\n",
       "      <td>日本</td>\n",
       "      <td>日语</td>\n",
       "      <td>121.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>超能陆战队</td>\n",
       "      <td>2014</td>\n",
       "      <td>8.7</td>\n",
       "      <td>810643.0</td>\n",
       "      <td>唐·霍尔 / 克里斯·威廉姆斯</td>\n",
       "      <td>乔丹·罗伯茨 / 丹尼尔·吉尔森 / 罗伯特·L·贝尔德</td>\n",
       "      <td>斯科特·安第斯 / 瑞恩·波特 / 丹尼尔·海尼 / T·J·米勒 / 杰米·钟 / 小达蒙...</td>\n",
       "      <td>喜剧 / 动作 / 科幻 / 动画 / 冒险</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>102.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>超能陆战队</td>\n",
       "      <td>2014</td>\n",
       "      <td>8.7</td>\n",
       "      <td>810643.0</td>\n",
       "      <td>唐·霍尔 / 克里斯·威廉姆斯</td>\n",
       "      <td>乔丹·罗伯茨 / 丹尼尔·吉尔森 / 罗伯特·L·贝尔德</td>\n",
       "      <td>斯科特·安第斯 / 瑞恩·波特 / 丹尼尔·海尼 / T·J·米勒 / 杰米·钟 / 小达蒙...</td>\n",
       "      <td>喜剧 / 动作 / 科幻 / 动画 / 冒险</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>102.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>超脱</td>\n",
       "      <td>2011</td>\n",
       "      <td>8.9</td>\n",
       "      <td>392204.0</td>\n",
       "      <td>托尼·凯耶</td>\n",
       "      <td>卡尔·隆德</td>\n",
       "      <td>艾德里安·布洛迪 / 马西娅·盖伊·哈登 / 詹姆斯·肯恩 / 克里斯蒂娜·亨德里克斯 / ...</td>\n",
       "      <td>剧情</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>超脱</td>\n",
       "      <td>2011</td>\n",
       "      <td>8.9</td>\n",
       "      <td>392204.0</td>\n",
       "      <td>托尼·凯耶</td>\n",
       "      <td>卡尔·隆德</td>\n",
       "      <td>艾德里安·布洛迪 / 马西娅·盖伊·哈登 / 詹姆斯·肯恩 / 克里斯蒂娜·亨德里克斯 / ...</td>\n",
       "      <td>剧情</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>97.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>重庆森林</td>\n",
       "      <td>1994</td>\n",
       "      <td>8.8</td>\n",
       "      <td>639120.0</td>\n",
       "      <td>王家卫</td>\n",
       "      <td>王家卫</td>\n",
       "      <td>林青霞 / 金城武 / 梁朝伟 / 王菲 / 周嘉玲</td>\n",
       "      <td>剧情 / 爱情</td>\n",
       "      <td>中国</td>\n",
       "      <td>粤语</td>\n",
       "      <td>102.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>重庆森林</td>\n",
       "      <td>1994</td>\n",
       "      <td>8.8</td>\n",
       "      <td>639120.0</td>\n",
       "      <td>王家卫</td>\n",
       "      <td>王家卫</td>\n",
       "      <td>林青霞 / 金城武 / 梁朝伟 / 王菲 / 周嘉玲</td>\n",
       "      <td>剧情 / 爱情</td>\n",
       "      <td>中国</td>\n",
       "      <td>粤语</td>\n",
       "      <td>102.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         片名  上映年份   评分      评价人数               导演  \\\n",
       "100    人生果实  2017  9.5  132229.0             伏原健之   \n",
       "128    人生果实  2017  9.5  132229.0             伏原健之   \n",
       "101    侧耳倾听  1995  8.9  371774.0             近藤喜文   \n",
       "129    侧耳倾听  1995  8.9  371774.0             近藤喜文   \n",
       "104    倩女幽魂  1987  8.7  591835.0              程小东   \n",
       "132    倩女幽魂  1987  8.7  591835.0              程小东   \n",
       "110     小森林  2014  9.0  341623.0              森淳一   \n",
       "122     小森林  2015  9.0  306686.0              森淳一   \n",
       "113    无人知晓  2004  9.1  233881.0             是枝裕和   \n",
       "130    无人知晓  2004  9.1  233881.0             是枝裕和   \n",
       "102    无人知晓  2004  9.1  233881.0             是枝裕和   \n",
       "111    无人知晓  2004  9.1  233881.0             是枝裕和   \n",
       "112    无人知晓  2004  9.1  233881.0             是枝裕和   \n",
       "133     甜蜜蜜  1996  NaN  420172.0              陈可辛   \n",
       "105     甜蜜蜜  1996  8.9  420172.0              陈可辛   \n",
       "127  菊次郎的夏天  1999  8.8  457770.0              北野武   \n",
       "99   菊次郎的夏天  1999  8.8  457770.0              北野武   \n",
       "103   超能陆战队  2014  8.7  810643.0  唐·霍尔 / 克里斯·威廉姆斯   \n",
       "131   超能陆战队  2014  8.7  810643.0  唐·霍尔 / 克里斯·威廉姆斯   \n",
       "119      超脱  2011  8.9  392204.0            托尼·凯耶   \n",
       "94       超脱  2011  8.9  392204.0            托尼·凯耶   \n",
       "116    重庆森林  1994  8.8  639120.0              王家卫   \n",
       "117    重庆森林  1994  8.8  639120.0              王家卫   \n",
       "\n",
       "                               编剧  \\\n",
       "100            津端修一 / 津端英子 / 树木希林   \n",
       "128            津端修一 / 津端英子 / 树木希林   \n",
       "101                      宫崎骏 / 柊葵   \n",
       "129                      宫崎骏 / 柊葵   \n",
       "104                           阮继志   \n",
       "132                           阮继志   \n",
       "110                   森淳一 / 五十岚大介   \n",
       "122                   森淳一 / 五十岚大介   \n",
       "113                          是枝裕和   \n",
       "130                          是枝裕和   \n",
       "102                          是枝裕和   \n",
       "111                          是枝裕和   \n",
       "112                          是枝裕和   \n",
       "133                            岸西   \n",
       "105                            岸西   \n",
       "127                           北野武   \n",
       "99                            北野武   \n",
       "103  乔丹·罗伯茨 / 丹尼尔·吉尔森 / 罗伯特·L·贝尔德   \n",
       "131  乔丹·罗伯茨 / 丹尼尔·吉尔森 / 罗伯特·L·贝尔德   \n",
       "119                         卡尔·隆德   \n",
       "94                          卡尔·隆德   \n",
       "116                           王家卫   \n",
       "117                           王家卫   \n",
       "\n",
       "                                                    主演  \\\n",
       "100                                                纪录片   \n",
       "128                                                纪录片   \n",
       "101  本名阳子 / 小林桂树 / 高山南 / 高桥一生 / 山下容莉枝 / 室井滋 / 露口茂 /...   \n",
       "129  本名阳子 / 小林桂树 / 高山南 / 高桥一生 / 山下容莉枝 / 室井滋 / 露口茂 /...   \n",
       "104         张国荣 / 王祖贤 / 午马 / 刘兆铭 / 林威 / 薛芷伦 / 胡大为 / 王晶   \n",
       "132         张国荣 / 王祖贤 / 午马 / 刘兆铭 / 林威 / 薛芷伦 / 胡大为 / 王晶   \n",
       "110                    桥本爱 / 三浦贵大 / 松冈茉优 / 温水洋一 / 桐岛加恋   \n",
       "122                    桥本爱 / 三浦贵大 / 松冈茉优 / 温水洋一 / 桐岛加恋   \n",
       "113  柳乐优弥 / 北浦爱 / 木村飞影 / 清水萌萌子 / 韩英惠 / 江原由希子 / 串田和美...   \n",
       "130  柳乐优弥 / 北浦爱 / 木村飞影 / 清水萌萌子 / 韩英惠 / 江原由希子 / 串田和美...   \n",
       "102  柳乐优弥 / 北浦爱 / 木村飞影 / 清水萌萌子 / 韩英惠 / 江原由希子 / 串田和美...   \n",
       "111  柳乐优弥 / 北浦爱 / 木村飞影 / 清水萌萌子 / 韩英惠 / 江原由希子 / 串田和美...   \n",
       "112  柳乐优弥 / 北浦爱 / 木村飞影 / 清水萌萌子 / 韩英惠 / 江原由希子 / 串田和美...   \n",
       "133        黎明 / 张曼玉 / 杨恭如 / 曾志伟 / 杜可风 / 张同祖 / 诸慧荷 / 丁羽   \n",
       "105        黎明 / 张曼玉 / 杨恭如 / 曾志伟 / 杜可风 / 张同祖 / 诸慧荷 / 丁羽   \n",
       "127  北野武 / 关口雄介 / 岸本加世子 / 吉行和子 / 细川典江 / 大家由祐子 / 磨赤儿...   \n",
       "99   北野武 / 关口雄介 / 岸本加世子 / 吉行和子 / 细川典江 / 大家由祐子 / 磨赤儿...   \n",
       "103  斯科特·安第斯 / 瑞恩·波特 / 丹尼尔·海尼 / T·J·米勒 / 杰米·钟 / 小达蒙...   \n",
       "131  斯科特·安第斯 / 瑞恩·波特 / 丹尼尔·海尼 / T·J·米勒 / 杰米·钟 / 小达蒙...   \n",
       "119  艾德里安·布洛迪 / 马西娅·盖伊·哈登 / 詹姆斯·肯恩 / 克里斯蒂娜·亨德里克斯 / ...   \n",
       "94   艾德里安·布洛迪 / 马西娅·盖伊·哈登 / 詹姆斯·肯恩 / 克里斯蒂娜·亨德里克斯 / ...   \n",
       "116                         林青霞 / 金城武 / 梁朝伟 / 王菲 / 周嘉玲   \n",
       "117                         林青霞 / 金城武 / 梁朝伟 / 王菲 / 周嘉玲   \n",
       "\n",
       "                         类型 国家/地区   语言  时长(分钟)  \n",
       "100      life-is-fruity.com    日本   日语    91.0  \n",
       "128      life-is-fruity.com    日本   日语    91.0  \n",
       "101            剧情 / 爱情 / 动画    日本  日语    111.0  \n",
       "129            剧情 / 爱情 / 动画    日本  日语    111.0  \n",
       "104       爱情 / 奇幻 / 武侠 / 古装    中国   粤语    98.0  \n",
       "132       爱情 / 奇幻 / 武侠 / 古装    中国   粤语    98.0  \n",
       "110                      剧情    日本   日语   111.0  \n",
       "122                      剧情    日本   日语   120.0  \n",
       "113                      剧情    日本   日语     NaN  \n",
       "130                      剧情    日本   日语   141.0  \n",
       "102                      剧情    日本   日语   141.0  \n",
       "111                      剧情    日本   日语   141.0  \n",
       "112                      剧情    日本   日语   141.0  \n",
       "133                 剧情 / 爱情    中国  粤语    118.0  \n",
       "105                 剧情 / 爱情    中国  粤语    118.0  \n",
       "127                 剧情 / 喜剧    日本   日语   121.0  \n",
       "99                  剧情 / 喜剧    日本   日语   121.0  \n",
       "103  喜剧 / 动作 / 科幻 / 动画 / 冒险    美国   英语   102.0  \n",
       "131  喜剧 / 动作 / 科幻 / 动画 / 冒险    美国   英语   102.0  \n",
       "119                      剧情    美国   英语    97.0  \n",
       "94                       剧情    美国   英语    97.0  \n",
       "116                 剧情 / 爱情    中国  粤语    102.0  \n",
       "117                 剧情 / 爱情    中国  粤语    102.0  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.片名.duplicated(keep=False)].sort_values('片名')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 20 - 删除重复值"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "删除全部的重复值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>片名</th>\n",
       "      <th>上映年份</th>\n",
       "      <th>评分</th>\n",
       "      <th>评价人数</th>\n",
       "      <th>导演</th>\n",
       "      <th>编剧</th>\n",
       "      <th>主演</th>\n",
       "      <th>类型</th>\n",
       "      <th>国家/地区</th>\n",
       "      <th>语言</th>\n",
       "      <th>时长(分钟)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>肖申克的救赎</td>\n",
       "      <td>1994</td>\n",
       "      <td>9.7</td>\n",
       "      <td>2317937.0</td>\n",
       "      <td>弗兰克·德拉邦特</td>\n",
       "      <td>弗兰克·德拉邦特 / 斯蒂芬·金</td>\n",
       "      <td>蒂姆·罗宾斯 / 摩根·弗里曼 / 鲍勃·冈顿 / 威廉姆·赛德勒 / 克兰西·布朗 / 吉...</td>\n",
       "      <td>剧情 / 犯罪</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>142.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>霸王别姬</td>\n",
       "      <td>1993</td>\n",
       "      <td>9.6</td>\n",
       "      <td>1720638.0</td>\n",
       "      <td>陈凯歌</td>\n",
       "      <td>芦苇 / 李碧华</td>\n",
       "      <td>张国荣 / 张丰毅 / 巩俐 / 葛优 / 英达 / 蒋雯丽 / 吴大维 / 吕齐 / 雷汉...</td>\n",
       "      <td>剧情 / 爱情 / 同性</td>\n",
       "      <td>中国</td>\n",
       "      <td>汉语普通话</td>\n",
       "      <td>171.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>阿甘正传</td>\n",
       "      <td>1994</td>\n",
       "      <td>9.5</td>\n",
       "      <td>1743966.0</td>\n",
       "      <td>罗伯特·泽米吉斯</td>\n",
       "      <td>艾瑞克·罗斯 / 温斯顿·格鲁姆</td>\n",
       "      <td>汤姆·汉克斯 / 罗宾·怀特 / 加里·西尼斯 / 麦凯尔泰·威廉逊 / 莎莉·菲尔德 / ...</td>\n",
       "      <td>剧情 / 爱情</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>142.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>这个杀手不太冷</td>\n",
       "      <td>1994</td>\n",
       "      <td>9.4</td>\n",
       "      <td>1922740.0</td>\n",
       "      <td>吕克·贝松</td>\n",
       "      <td>吕克·贝松</td>\n",
       "      <td>让·雷诺 / 娜塔莉·波特曼 / 加里·奥德曼 / 丹尼·爱罗 / 彼得·阿佩尔 / 迈克尔...</td>\n",
       "      <td>剧情 / 动作 / 犯罪</td>\n",
       "      <td>法国</td>\n",
       "      <td>英语</td>\n",
       "      <td>110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>泰坦尼克号</td>\n",
       "      <td>1997</td>\n",
       "      <td>9.4</td>\n",
       "      <td>1706127.0</td>\n",
       "      <td>詹姆斯·卡梅隆</td>\n",
       "      <td>詹姆斯·卡梅隆</td>\n",
       "      <td>莱昂纳多·迪卡普里奥 / 凯特·温丝莱特 / 比利·赞恩 / 凯西·贝茨 / 弗兰西丝·费舍...</td>\n",
       "      <td>剧情 / 爱情 / 灾难</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>194.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>257</th>\n",
       "      <td>浪潮</td>\n",
       "      <td>2008</td>\n",
       "      <td>8.7</td>\n",
       "      <td>223511.0</td>\n",
       "      <td>丹尼斯·甘塞尔</td>\n",
       "      <td>丹尼斯·甘塞尔 / 彼得·图万斯 / 约翰尼·道金斯 / 罗恩·比恩巴赫 / 罗恩·琼斯</td>\n",
       "      <td>于尔根·福格尔 / 弗雷德里克·劳 / 马克思·雷迈特 / 詹妮弗·乌尔里希 / 克里斯蒂安...</td>\n",
       "      <td>剧情 / 惊悚</td>\n",
       "      <td>NaN</td>\n",
       "      <td>德语</td>\n",
       "      <td>107.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>258</th>\n",
       "      <td>小萝莉的猴神大叔</td>\n",
       "      <td>2015</td>\n",
       "      <td>8.4</td>\n",
       "      <td>404886.0</td>\n",
       "      <td>卡比尔·汗</td>\n",
       "      <td>卡比尔·汗 / 维杰耶德拉·普拉萨德</td>\n",
       "      <td>萨尔曼·汗 / 哈莎莉·马洛特拉 / 卡琳娜·卡普尔 / 纳瓦祖丁·席迪圭 / 欧姆·普瑞 ...</td>\n",
       "      <td>剧情 / 喜剧 / 动作</td>\n",
       "      <td>印度</td>\n",
       "      <td>印地语</td>\n",
       "      <td>159.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>259</th>\n",
       "      <td>追随</td>\n",
       "      <td>1998</td>\n",
       "      <td>8.9</td>\n",
       "      <td>149521.0</td>\n",
       "      <td>克里斯托弗·诺兰</td>\n",
       "      <td>克里斯托弗·诺兰</td>\n",
       "      <td>杰里米·西奥伯德 / 亚历克斯·霍 / 露西·拉塞尔 / 约翰·诺兰 / 迪克·布拉德塞尔 ...</td>\n",
       "      <td>悬疑 / 惊悚 / 犯罪</td>\n",
       "      <td>英国</td>\n",
       "      <td>英语</td>\n",
       "      <td>69.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260</th>\n",
       "      <td>网络谜踪</td>\n",
       "      <td>2018</td>\n",
       "      <td>8.6</td>\n",
       "      <td>430811.0</td>\n",
       "      <td>阿尼什·查甘蒂</td>\n",
       "      <td>阿尼什·查甘蒂 / 赛弗·奥哈尼安</td>\n",
       "      <td>约翰·赵 / 米切尔·拉 / 黛博拉·梅辛 / 约瑟夫·李 / 萨拉·米博·孙 / 亚历克丝...</td>\n",
       "      <td>剧情 / 悬疑 / 惊悚 / 犯罪</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>102.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261</th>\n",
       "      <td>黑鹰坠落</td>\n",
       "      <td>2001</td>\n",
       "      <td>8.7</td>\n",
       "      <td>239402.0</td>\n",
       "      <td>雷德利·斯科特</td>\n",
       "      <td>肯·诺兰 / 马克·鲍登</td>\n",
       "      <td>乔什·哈奈特 / 伊万·麦克格雷格 / 汤姆·塞兹摩尔 / 金·寇兹 / 艾文·布莱纳 / ...</td>\n",
       "      <td>动作 / 历史 / 战争</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>144.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>244 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           片名  上映年份   评分       评价人数        导演  \\\n",
       "0      肖申克的救赎  1994  9.7  2317937.0  弗兰克·德拉邦特   \n",
       "1        霸王别姬  1993  9.6  1720638.0       陈凯歌   \n",
       "2        阿甘正传  1994  9.5  1743966.0  罗伯特·泽米吉斯   \n",
       "3     这个杀手不太冷  1994  9.4  1922740.0     吕克·贝松   \n",
       "4       泰坦尼克号  1997  9.4  1706127.0   詹姆斯·卡梅隆   \n",
       "..        ...   ...  ...        ...       ...   \n",
       "257        浪潮  2008  8.7   223511.0   丹尼斯·甘塞尔   \n",
       "258  小萝莉的猴神大叔  2015  8.4   404886.0     卡比尔·汗   \n",
       "259        追随  1998  8.9   149521.0  克里斯托弗·诺兰   \n",
       "260      网络谜踪  2018  8.6   430811.0   阿尼什·查甘蒂   \n",
       "261      黑鹰坠落  2001  8.7   239402.0   雷德利·斯科特   \n",
       "\n",
       "                                               编剧  \\\n",
       "0                                弗兰克·德拉邦特 / 斯蒂芬·金   \n",
       "1                                        芦苇 / 李碧华   \n",
       "2                                艾瑞克·罗斯 / 温斯顿·格鲁姆   \n",
       "3                                           吕克·贝松   \n",
       "4                                         詹姆斯·卡梅隆   \n",
       "..                                            ...   \n",
       "257  丹尼斯·甘塞尔 / 彼得·图万斯 / 约翰尼·道金斯 / 罗恩·比恩巴赫 / 罗恩·琼斯   \n",
       "258                            卡比尔·汗 / 维杰耶德拉·普拉萨德   \n",
       "259                                      克里斯托弗·诺兰   \n",
       "260                             阿尼什·查甘蒂 / 赛弗·奥哈尼安   \n",
       "261                                  肯·诺兰 / 马克·鲍登   \n",
       "\n",
       "                                                    主演                 类型  \\\n",
       "0    蒂姆·罗宾斯 / 摩根·弗里曼 / 鲍勃·冈顿 / 威廉姆·赛德勒 / 克兰西·布朗 / 吉...            剧情 / 犯罪   \n",
       "1    张国荣 / 张丰毅 / 巩俐 / 葛优 / 英达 / 蒋雯丽 / 吴大维 / 吕齐 / 雷汉...       剧情 / 爱情 / 同性   \n",
       "2    汤姆·汉克斯 / 罗宾·怀特 / 加里·西尼斯 / 麦凯尔泰·威廉逊 / 莎莉·菲尔德 / ...            剧情 / 爱情   \n",
       "3    让·雷诺 / 娜塔莉·波特曼 / 加里·奥德曼 / 丹尼·爱罗 / 彼得·阿佩尔 / 迈克尔...       剧情 / 动作 / 犯罪   \n",
       "4    莱昂纳多·迪卡普里奥 / 凯特·温丝莱特 / 比利·赞恩 / 凯西·贝茨 / 弗兰西丝·费舍...       剧情 / 爱情 / 灾难   \n",
       "..                                                 ...                ...   \n",
       "257  于尔根·福格尔 / 弗雷德里克·劳 / 马克思·雷迈特 / 詹妮弗·乌尔里希 / 克里斯蒂安...            剧情 / 惊悚   \n",
       "258  萨尔曼·汗 / 哈莎莉·马洛特拉 / 卡琳娜·卡普尔 / 纳瓦祖丁·席迪圭 / 欧姆·普瑞 ...       剧情 / 喜剧 / 动作   \n",
       "259  杰里米·西奥伯德 / 亚历克斯·霍 / 露西·拉塞尔 / 约翰·诺兰 / 迪克·布拉德塞尔 ...       悬疑 / 惊悚 / 犯罪   \n",
       "260  约翰·赵 / 米切尔·拉 / 黛博拉·梅辛 / 约瑟夫·李 / 萨拉·米博·孙 / 亚历克丝...  剧情 / 悬疑 / 惊悚 / 犯罪   \n",
       "261  乔什·哈奈特 / 伊万·麦克格雷格 / 汤姆·塞兹摩尔 / 金·寇兹 / 艾文·布莱纳 / ...       动作 / 历史 / 战争   \n",
       "\n",
       "    国家/地区     语言  时长(分钟)  \n",
       "0      美国     英语   142.0  \n",
       "1      中国  汉语普通话   171.0  \n",
       "2      美国     英语   142.0  \n",
       "3      法国    英语    110.0  \n",
       "4      美国    英语    194.0  \n",
       "..    ...    ...     ...  \n",
       "257   NaN     德语   107.0  \n",
       "258    印度   印地语    159.0  \n",
       "259    英国     英语    69.0  \n",
       "260    美国     英语   102.0  \n",
       "261    美国    英语    144.0  \n",
       "\n",
       "[244 rows x 11 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.drop_duplicates(keep=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 21 - 删除重复值｜指定"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "删除全部的重复值，但保留最后一次出现的值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>片名</th>\n",
       "      <th>上映年份</th>\n",
       "      <th>评分</th>\n",
       "      <th>评价人数</th>\n",
       "      <th>导演</th>\n",
       "      <th>编剧</th>\n",
       "      <th>主演</th>\n",
       "      <th>类型</th>\n",
       "      <th>国家/地区</th>\n",
       "      <th>语言</th>\n",
       "      <th>时长(分钟)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>肖申克的救赎</td>\n",
       "      <td>1994</td>\n",
       "      <td>9.7</td>\n",
       "      <td>2317937.0</td>\n",
       "      <td>弗兰克·德拉邦特</td>\n",
       "      <td>弗兰克·德拉邦特 / 斯蒂芬·金</td>\n",
       "      <td>蒂姆·罗宾斯 / 摩根·弗里曼 / 鲍勃·冈顿 / 威廉姆·赛德勒 / 克兰西·布朗 / 吉...</td>\n",
       "      <td>剧情 / 犯罪</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>142.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>霸王别姬</td>\n",
       "      <td>1993</td>\n",
       "      <td>9.6</td>\n",
       "      <td>1720638.0</td>\n",
       "      <td>陈凯歌</td>\n",
       "      <td>芦苇 / 李碧华</td>\n",
       "      <td>张国荣 / 张丰毅 / 巩俐 / 葛优 / 英达 / 蒋雯丽 / 吴大维 / 吕齐 / 雷汉...</td>\n",
       "      <td>剧情 / 爱情 / 同性</td>\n",
       "      <td>中国</td>\n",
       "      <td>汉语普通话</td>\n",
       "      <td>171.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>阿甘正传</td>\n",
       "      <td>1994</td>\n",
       "      <td>9.5</td>\n",
       "      <td>1743966.0</td>\n",
       "      <td>罗伯特·泽米吉斯</td>\n",
       "      <td>艾瑞克·罗斯 / 温斯顿·格鲁姆</td>\n",
       "      <td>汤姆·汉克斯 / 罗宾·怀特 / 加里·西尼斯 / 麦凯尔泰·威廉逊 / 莎莉·菲尔德 / ...</td>\n",
       "      <td>剧情 / 爱情</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>142.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>这个杀手不太冷</td>\n",
       "      <td>1994</td>\n",
       "      <td>9.4</td>\n",
       "      <td>1922740.0</td>\n",
       "      <td>吕克·贝松</td>\n",
       "      <td>吕克·贝松</td>\n",
       "      <td>让·雷诺 / 娜塔莉·波特曼 / 加里·奥德曼 / 丹尼·爱罗 / 彼得·阿佩尔 / 迈克尔...</td>\n",
       "      <td>剧情 / 动作 / 犯罪</td>\n",
       "      <td>法国</td>\n",
       "      <td>英语</td>\n",
       "      <td>110.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>泰坦尼克号</td>\n",
       "      <td>1997</td>\n",
       "      <td>9.4</td>\n",
       "      <td>1706127.0</td>\n",
       "      <td>詹姆斯·卡梅隆</td>\n",
       "      <td>詹姆斯·卡梅隆</td>\n",
       "      <td>莱昂纳多·迪卡普里奥 / 凯特·温丝莱特 / 比利·赞恩 / 凯西·贝茨 / 弗兰西丝·费舍...</td>\n",
       "      <td>剧情 / 爱情 / 灾难</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>194.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>257</th>\n",
       "      <td>浪潮</td>\n",
       "      <td>2008</td>\n",
       "      <td>8.7</td>\n",
       "      <td>223511.0</td>\n",
       "      <td>丹尼斯·甘塞尔</td>\n",
       "      <td>丹尼斯·甘塞尔 / 彼得·图万斯 / 约翰尼·道金斯 / 罗恩·比恩巴赫 / 罗恩·琼斯</td>\n",
       "      <td>于尔根·福格尔 / 弗雷德里克·劳 / 马克思·雷迈特 / 詹妮弗·乌尔里希 / 克里斯蒂安...</td>\n",
       "      <td>剧情 / 惊悚</td>\n",
       "      <td>NaN</td>\n",
       "      <td>德语</td>\n",
       "      <td>107.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>258</th>\n",
       "      <td>小萝莉的猴神大叔</td>\n",
       "      <td>2015</td>\n",
       "      <td>8.4</td>\n",
       "      <td>404886.0</td>\n",
       "      <td>卡比尔·汗</td>\n",
       "      <td>卡比尔·汗 / 维杰耶德拉·普拉萨德</td>\n",
       "      <td>萨尔曼·汗 / 哈莎莉·马洛特拉 / 卡琳娜·卡普尔 / 纳瓦祖丁·席迪圭 / 欧姆·普瑞 ...</td>\n",
       "      <td>剧情 / 喜剧 / 动作</td>\n",
       "      <td>印度</td>\n",
       "      <td>印地语</td>\n",
       "      <td>159.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>259</th>\n",
       "      <td>追随</td>\n",
       "      <td>1998</td>\n",
       "      <td>8.9</td>\n",
       "      <td>149521.0</td>\n",
       "      <td>克里斯托弗·诺兰</td>\n",
       "      <td>克里斯托弗·诺兰</td>\n",
       "      <td>杰里米·西奥伯德 / 亚历克斯·霍 / 露西·拉塞尔 / 约翰·诺兰 / 迪克·布拉德塞尔 ...</td>\n",
       "      <td>悬疑 / 惊悚 / 犯罪</td>\n",
       "      <td>英国</td>\n",
       "      <td>英语</td>\n",
       "      <td>69.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260</th>\n",
       "      <td>网络谜踪</td>\n",
       "      <td>2018</td>\n",
       "      <td>8.6</td>\n",
       "      <td>430811.0</td>\n",
       "      <td>阿尼什·查甘蒂</td>\n",
       "      <td>阿尼什·查甘蒂 / 赛弗·奥哈尼安</td>\n",
       "      <td>约翰·赵 / 米切尔·拉 / 黛博拉·梅辛 / 约瑟夫·李 / 萨拉·米博·孙 / 亚历克丝...</td>\n",
       "      <td>剧情 / 悬疑 / 惊悚 / 犯罪</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>102.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261</th>\n",
       "      <td>黑鹰坠落</td>\n",
       "      <td>2001</td>\n",
       "      <td>8.7</td>\n",
       "      <td>239402.0</td>\n",
       "      <td>雷德利·斯科特</td>\n",
       "      <td>肯·诺兰 / 马克·鲍登</td>\n",
       "      <td>乔什·哈奈特 / 伊万·麦克格雷格 / 汤姆·塞兹摩尔 / 金·寇兹 / 艾文·布莱纳 / ...</td>\n",
       "      <td>动作 / 历史 / 战争</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>144.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>249 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           片名  上映年份   评分       评价人数        导演  \\\n",
       "0      肖申克的救赎  1994  9.7  2317937.0  弗兰克·德拉邦特   \n",
       "1        霸王别姬  1993  9.6  1720638.0       陈凯歌   \n",
       "2        阿甘正传  1994  9.5  1743966.0  罗伯特·泽米吉斯   \n",
       "3     这个杀手不太冷  1994  9.4  1922740.0     吕克·贝松   \n",
       "4       泰坦尼克号  1997  9.4  1706127.0   詹姆斯·卡梅隆   \n",
       "..        ...   ...  ...        ...       ...   \n",
       "257        浪潮  2008  8.7   223511.0   丹尼斯·甘塞尔   \n",
       "258  小萝莉的猴神大叔  2015  8.4   404886.0     卡比尔·汗   \n",
       "259        追随  1998  8.9   149521.0  克里斯托弗·诺兰   \n",
       "260      网络谜踪  2018  8.6   430811.0   阿尼什·查甘蒂   \n",
       "261      黑鹰坠落  2001  8.7   239402.0   雷德利·斯科特   \n",
       "\n",
       "                                               编剧  \\\n",
       "0                                弗兰克·德拉邦特 / 斯蒂芬·金   \n",
       "1                                        芦苇 / 李碧华   \n",
       "2                                艾瑞克·罗斯 / 温斯顿·格鲁姆   \n",
       "3                                           吕克·贝松   \n",
       "4                                         詹姆斯·卡梅隆   \n",
       "..                                            ...   \n",
       "257  丹尼斯·甘塞尔 / 彼得·图万斯 / 约翰尼·道金斯 / 罗恩·比恩巴赫 / 罗恩·琼斯   \n",
       "258                            卡比尔·汗 / 维杰耶德拉·普拉萨德   \n",
       "259                                      克里斯托弗·诺兰   \n",
       "260                             阿尼什·查甘蒂 / 赛弗·奥哈尼安   \n",
       "261                                  肯·诺兰 / 马克·鲍登   \n",
       "\n",
       "                                                    主演                 类型  \\\n",
       "0    蒂姆·罗宾斯 / 摩根·弗里曼 / 鲍勃·冈顿 / 威廉姆·赛德勒 / 克兰西·布朗 / 吉...            剧情 / 犯罪   \n",
       "1    张国荣 / 张丰毅 / 巩俐 / 葛优 / 英达 / 蒋雯丽 / 吴大维 / 吕齐 / 雷汉...       剧情 / 爱情 / 同性   \n",
       "2    汤姆·汉克斯 / 罗宾·怀特 / 加里·西尼斯 / 麦凯尔泰·威廉逊 / 莎莉·菲尔德 / ...            剧情 / 爱情   \n",
       "3    让·雷诺 / 娜塔莉·波特曼 / 加里·奥德曼 / 丹尼·爱罗 / 彼得·阿佩尔 / 迈克尔...       剧情 / 动作 / 犯罪   \n",
       "4    莱昂纳多·迪卡普里奥 / 凯特·温丝莱特 / 比利·赞恩 / 凯西·贝茨 / 弗兰西丝·费舍...       剧情 / 爱情 / 灾难   \n",
       "..                                                 ...                ...   \n",
       "257  于尔根·福格尔 / 弗雷德里克·劳 / 马克思·雷迈特 / 詹妮弗·乌尔里希 / 克里斯蒂安...            剧情 / 惊悚   \n",
       "258  萨尔曼·汗 / 哈莎莉·马洛特拉 / 卡琳娜·卡普尔 / 纳瓦祖丁·席迪圭 / 欧姆·普瑞 ...       剧情 / 喜剧 / 动作   \n",
       "259  杰里米·西奥伯德 / 亚历克斯·霍 / 露西·拉塞尔 / 约翰·诺兰 / 迪克·布拉德塞尔 ...       悬疑 / 惊悚 / 犯罪   \n",
       "260  约翰·赵 / 米切尔·拉 / 黛博拉·梅辛 / 约瑟夫·李 / 萨拉·米博·孙 / 亚历克丝...  剧情 / 悬疑 / 惊悚 / 犯罪   \n",
       "261  乔什·哈奈特 / 伊万·麦克格雷格 / 汤姆·塞兹摩尔 / 金·寇兹 / 艾文·布莱纳 / ...       动作 / 历史 / 战争   \n",
       "\n",
       "    国家/地区     语言  时长(分钟)  \n",
       "0      美国     英语   142.0  \n",
       "1      中国  汉语普通话   171.0  \n",
       "2      美国     英语   142.0  \n",
       "3      法国    英语    110.0  \n",
       "4      美国    英语    194.0  \n",
       "..    ...    ...     ...  \n",
       "257   NaN     德语   107.0  \n",
       "258    印度   印地语    159.0  \n",
       "259    英国     英语    69.0  \n",
       "260    美国     英语   102.0  \n",
       "261    美国    英语    144.0  \n",
       "\n",
       "[249 rows x 11 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#df[df.片名.duplicated(keep='last')]\n",
    "df.drop_duplicates('片名', keep='last')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop_duplicates('片名', keep='first', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import sys\n",
    "\n",
    "# 中文\n",
    "if sys.platform == 'darwin':\n",
    "    plt.rcParams['font.sans-serif']=['Songti SC'] \n",
    "else:\n",
    "    plt.rcParams['font.sans-serif']=['SimHei'] \n",
    "    \n",
    "plt.rcParams['axes.unicode_minus']=False\n",
    "\n",
    "plt.style.use('ggplot')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 4.81 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "df2 = pd.DataFrame({'actor':[], 'movie':[]})\n",
    "o = {'actor':'', 'movie':''}\n",
    "\n",
    "for k, row in df.iterrows():\n",
    "    acts =  [s.strip() for s in row.主演.split('/')]\n",
    "    #print(len(acts))\n",
    "    for act in acts:\n",
    "        o['actor'] = act\n",
    "        o['movie'] = row.片名\n",
    "        df2 = df2.append(o,ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 4.99 ms\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "movie\n",
       "2001太空漫游        凯尔·杜拉,加里·洛克伍德,威廉姆·西尔维斯特,丹尼尔·里希特,雷纳德·洛塞特,罗伯特·比提...\n",
       "7号房的礼物                            柳承龙,朴信惠,郑镇荣,金正泰,吴达洙,朴元尚,郑满植,葛素媛\n",
       "一一              吴念真,李凯莉,金燕玲,张洋洋,萧淑慎,尾形一成,陈希圣,林孟瑾,陈以文,柯宇纶,张育邦,柯...\n",
       "一个叫欧维的男人决定去死    罗夫·拉斯加德,巴哈·帕斯,托比亚斯·阿姆博瑞,菲利普·伯格,安娜-莱娜·布伦丁,博瑞·伦贝...\n",
       "七宗罪             摩根·弗里曼,布拉德·皮特,凯文·史派西,格温妮斯·帕特洛,安德鲁·凯文·沃克,约翰·卡西尼...\n",
       "                                      ...                        \n",
       "黑客帝国            基努·里维斯,劳伦斯·菲什伯恩,凯瑞-安·莫斯,雨果·维文,格洛丽亚·福斯特,乔·潘托里亚诺...\n",
       "黑客帝国2：重装上阵      基努·里维斯,劳伦斯·菲什伯恩,凯瑞-安·莫斯,雨果·维文,莫妮卡·贝鲁奇,赫尔穆特·巴凯蒂...\n",
       "黑客帝国3：矩阵革命      基努·里维斯,劳伦斯·菲什伯恩,凯瑞-安·莫斯,雨果·维文,贾达·萍克·史密斯,凯特·宾汉,...\n",
       "黑鹰坠落            乔什·哈奈特,伊万·麦克格雷格,汤姆·塞兹摩尔,金·寇兹,艾文·布莱纳,艾瑞克·巴纳,休·丹...\n",
       "龙猫              日高法子,坂本千夏,糸井重里,岛本须美,北林谷荣,高木均,雨笠利幸,丸山裕子,广濑正志,鹫尾...\n",
       "Name: actor, Length: 249, dtype: object"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "df2.groupby('movie').actor.apply(lambda x: ','.join(x))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 16 ms\n"
     ]
    },
    {
     "data": {
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       "  <tbody>\n",
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       "      <th>哈利·波特与火焰杯</th>\n",
       "      <td>67</td>\n",
       "      <td>丹尼尔·雷德克里夫,艾玛·沃森,鲁伯特·格林特,迈克尔·刚本,玛吉·史密斯,汤姆·费尔顿,蒂...</td>\n",
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       "      <th>拯救大兵瑞恩</th>\n",
       "      <td>48</td>\n",
       "      <td>汤姆·汉克斯,汤姆·塞兹摩尔,爱德华·伯恩斯,巴里·佩珀,亚当·戈德堡,范·迪塞尔,吉奥瓦尼...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>七武士</th>\n",
       "      <td>47</td>\n",
       "      <td>三船敏郎,志村乔,津岛惠子,岛崎雪子,藤原釜足,加东大介,木村功,千秋实,宫口精二,小杉义男...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>美丽心灵</th>\n",
       "      <td>46</td>\n",
       "      <td>罗素·克劳,艾德·哈里斯,詹妮弗·康纳利,克里斯托弗·普卢默,保罗·贝坦尼,亚当·戈德堡,乔...</td>\n",
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       "      <td>基努·里维斯,劳伦斯·菲什伯恩,凯瑞-安·莫斯,雨果·维文,莫妮卡·贝鲁奇,赫尔穆特·巴凯蒂...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>泰坦尼克号</th>\n",
       "      <td>44</td>\n",
       "      <td>莱昂纳多·迪卡普里奥,凯特·温丝莱特,比利·赞恩,凯西·贝茨,弗兰西丝·费舍,格劳瑞亚·斯图...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>阿甘正传</th>\n",
       "      <td>41</td>\n",
       "      <td>汤姆·汉克斯,罗宾·怀特,加里·西尼斯,麦凯尔泰·威廉逊,莎莉·菲尔德,海利·乔·奥斯蒙,迈...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>终结者2：审判日</th>\n",
       "      <td>39</td>\n",
       "      <td>阿诺·施瓦辛格,琳达·汉密尔顿,爱德华·福隆,罗伯特·帕特里克,阿尔·伯恩,乔·莫顿,埃帕莎...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>指环王1：魔戒再现</th>\n",
       "      <td>38</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>东京教父</th>\n",
       "      <td>37</td>\n",
       "      <td>江守彻,梅垣义明,冈本绫,饭塚昭三,加藤精三,石丸博也,槐柳二,屋良有作,寺濑今日子,能登麻...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>黑客帝国3：矩阵革命</th>\n",
       "      <td>34</td>\n",
       "      <td>基努·里维斯,劳伦斯·菲什伯恩,凯瑞-安·莫斯,雨果·维文,贾达·萍克·史密斯,凯特·宾汉,...</td>\n",
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      ],
      "text/plain": [
       "            size                                           <lambda>\n",
       "           actor                                              actor\n",
       "movie                                                              \n",
       "哈利·波特与火焰杯     67  丹尼尔·雷德克里夫,艾玛·沃森,鲁伯特·格林特,迈克尔·刚本,玛吉·史密斯,汤姆·费尔顿,蒂...\n",
       "指环王3：王者无敌     63  伊利亚·伍德,西恩·奥斯汀,维果·莫腾森,奥兰多·布鲁姆,伊恩·麦克莱恩,肖恩·宾,多米尼克...\n",
       "教父2           62  阿尔·帕西诺,罗伯特·杜瓦尔,黛安·基顿,罗伯特·德尼罗,约翰·凯泽尔,塔莉娅·夏尔,李·斯...\n",
       "魂断蓝桥          59  费雯·丽,罗伯特·泰勒,露塞尔·沃特森,弗吉尼亚·菲尔德,玛丽亚·彭斯卡娅,C.奥布雷·史密...\n",
       "雨中曲           53  吉恩·凯利,唐纳德·奥康纳,黛比·雷诺斯,简·哈根,米勒德·米切尔,赛德·查里斯,达格拉斯·...\n",
       "幸福终点站         51  汤姆·汉克斯,凯瑟琳·泽塔-琼斯,斯坦利·图齐,齐·麦克布赖德,迭戈·卢纳,巴里·沙巴卡·亨...\n",
       "指环王2：双塔奇兵     51  伊利亚·伍德,西恩·奥斯汀,多米尼克·莫纳汉,奥兰多·布鲁姆,维果·莫腾森,伊恩·麦克莱恩,...\n",
       "拯救大兵瑞恩        48  汤姆·汉克斯,汤姆·塞兹摩尔,爱德华·伯恩斯,巴里·佩珀,亚当·戈德堡,范·迪塞尔,吉奥瓦尼...\n",
       "七武士           47  三船敏郎,志村乔,津岛惠子,岛崎雪子,藤原釜足,加东大介,木村功,千秋实,宫口精二,小杉义男...\n",
       "美丽心灵          46  罗素·克劳,艾德·哈里斯,詹妮弗·康纳利,克里斯托弗·普卢默,保罗·贝坦尼,亚当·戈德堡,乔...\n",
       "黑客帝国2：重装上阵    46  基努·里维斯,劳伦斯·菲什伯恩,凯瑞-安·莫斯,雨果·维文,莫妮卡·贝鲁奇,赫尔穆特·巴凯蒂...\n",
       "泰坦尼克号         44  莱昂纳多·迪卡普里奥,凯特·温丝莱特,比利·赞恩,凯西·贝茨,弗兰西丝·费舍,格劳瑞亚·斯图...\n",
       "阿甘正传          41  汤姆·汉克斯,罗宾·怀特,加里·西尼斯,麦凯尔泰·威廉逊,莎莉·菲尔德,海利·乔·奥斯蒙,迈...\n",
       "终结者2：审判日      39  阿诺·施瓦辛格,琳达·汉密尔顿,爱德华·福隆,罗伯特·帕特里克,阿尔·伯恩,乔·莫顿,埃帕莎...\n",
       "指环王1：魔戒再现     38  伊利亚·伍德,西恩·奥斯汀,伊恩·麦克莱恩,奥兰多·布鲁姆,维果·莫腾森,多米尼克·莫纳汉,...\n",
       "时空恋旅人         37  多姆纳尔·格里森,瑞秋·麦克亚当斯,比尔·奈伊,莉迪亚·威尔逊,琳赛·邓肯,理查德·科德里,...\n",
       "无敌破坏王         37  约翰·C·赖利,萨拉·西尔弗曼,杰克·麦克布瑞尔,简·林奇,艾伦·图代克,敏迪·卡灵,乔·洛...\n",
       "摩登时代          37  查理·卓别林,宝莲·高黛,亨利·伯格曼,蒂尼·桑福德,切斯特·康克林,汉克·曼,斯坦利·布莱...\n",
       "东京教父          37  江守彻,梅垣义明,冈本绫,饭塚昭三,加藤精三,石丸博也,槐柳二,屋良有作,寺濑今日子,能登麻...\n",
       "黑客帝国3：矩阵革命    34  基努·里维斯,劳伦斯·菲什伯恩,凯瑞-安·莫斯,雨果·维文,贾达·萍克·史密斯,凯特·宾汉,..."
      ]
     },
     "execution_count": 146,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "df2.pivot_table(index='movie', values='actor', aggfunc=[np.size,lambda x: ','.join(x)]).sort_values(('size','actor'), ascending=False)[:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [
    {
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       "      <td>弗朗西斯·福特·科波拉</td>\n",
       "      <td>弗朗西斯·福特·科波拉 / 马里奥·普佐</td>\n",
       "      <td>阿尔·帕西诺 / 罗伯特·杜瓦尔 / 黛安·基顿 / 罗伯特·德尼罗 / 约翰·凯泽尔 / ...</td>\n",
       "      <td>剧情 / 犯罪</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>202.0</td>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224</th>\n",
       "      <td>魂断蓝桥</td>\n",
       "      <td>1940</td>\n",
       "      <td>8.8</td>\n",
       "      <td>225318.0</td>\n",
       "      <td>茂文·勒鲁瓦</td>\n",
       "      <td>塞缪尔·N·贝尔曼 / 汉斯·拉莫 / 乔治·弗罗斯切尔 / 罗伯特·E·舍伍德</td>\n",
       "      <td>费雯·丽 / 罗伯特·泰勒 / 露塞尔·沃特森 / 弗吉尼亚·菲尔德 / 玛丽亚·彭斯卡娅 ...</td>\n",
       "      <td>剧情 / 爱情 / 战争</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>108.0</td>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208</th>\n",
       "      <td>雨中曲</td>\n",
       "      <td>1952</td>\n",
       "      <td>9.0</td>\n",
       "      <td>167372.0</td>\n",
       "      <td>斯坦利·多南 / 吉恩·凯利</td>\n",
       "      <td>贝蒂·康登 / 阿多夫·格林</td>\n",
       "      <td>吉恩·凯利 / 唐纳德·奥康纳 / 黛比·雷诺斯 / 简·哈根 / 米勒德·米切尔 / 赛德...</td>\n",
       "      <td>喜剧 / 爱情 / 歌舞</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>103.0</td>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>幸福终点站</td>\n",
       "      <td>2004</td>\n",
       "      <td>8.8</td>\n",
       "      <td>440640.0</td>\n",
       "      <td>史蒂文·斯皮尔伯格</td>\n",
       "      <td>安德鲁·尼科尔 / 萨沙·杰瓦西  / 杰夫·内桑森</td>\n",
       "      <td>汤姆·汉克斯 / 凯瑟琳·泽塔-琼斯 / 斯坦利·图齐 / 齐·麦克布赖德 / 迭戈·卢纳 ...</td>\n",
       "      <td>剧情 / 喜剧 / 爱情</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>128.0</td>\n",
       "      <td>51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>指环王2：双塔奇兵</td>\n",
       "      <td>2002</td>\n",
       "      <td>9.1</td>\n",
       "      <td>560238.0</td>\n",
       "      <td>彼得·杰克逊</td>\n",
       "      <td>弗兰·威尔士 / 菲利帕·鲍恩斯 / 斯蒂芬·辛克莱 / 彼得·杰克逊 / J·R·R·托尔金</td>\n",
       "      <td>伊利亚·伍德 / 西恩·奥斯汀 / 多米尼克·莫纳汉 / 奥兰多·布鲁姆 / 维果·莫腾森 ...</td>\n",
       "      <td>剧情 / 动作 / 奇幻 / 冒险</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>179.0</td>\n",
       "      <td>51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>拯救大兵瑞恩</td>\n",
       "      <td>1998</td>\n",
       "      <td>9.0</td>\n",
       "      <td>520707.0</td>\n",
       "      <td>史蒂文·斯皮尔伯格</td>\n",
       "      <td>罗伯特·罗达特</td>\n",
       "      <td>汤姆·汉克斯 / 汤姆·塞兹摩尔 / 爱德华·伯恩斯 / 巴里·佩珀 / 亚当·戈德堡 / ...</td>\n",
       "      <td>剧情 / 战争</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>169.0</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>七武士</td>\n",
       "      <td>1954</td>\n",
       "      <td>9.3</td>\n",
       "      <td>153914.0</td>\n",
       "      <td>黑泽明</td>\n",
       "      <td>黑泽明 / 桥本忍 / 小国英雄</td>\n",
       "      <td>三船敏郎 / 志村乔 / 津岛惠子 / 岛崎雪子 / 藤原釜足 / 加东大介 / 木村功 /...</td>\n",
       "      <td>剧情 / 动作 / 冒险</td>\n",
       "      <td>日本</td>\n",
       "      <td>日语</td>\n",
       "      <td>207.0</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>美丽心灵</td>\n",
       "      <td>2001</td>\n",
       "      <td>9.0</td>\n",
       "      <td>611950.0</td>\n",
       "      <td>朗·霍华德</td>\n",
       "      <td>阿齐瓦·高斯曼 / 西尔维娅·纳萨尔</td>\n",
       "      <td>罗素·克劳 / 艾德·哈里斯 / 詹妮弗·康纳利 / 克里斯托弗·普卢默 / 保罗·贝坦尼 ...</td>\n",
       "      <td>剧情 / 传记</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>135.0</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>黑客帝国2：重装上阵</td>\n",
       "      <td>2003</td>\n",
       "      <td>8.6</td>\n",
       "      <td>305302.0</td>\n",
       "      <td>莉莉·沃卓斯基 / 拉娜·沃卓斯基</td>\n",
       "      <td>莉莉·沃卓斯基 / 拉娜·沃卓斯基</td>\n",
       "      <td>基努·里维斯 / 劳伦斯·菲什伯恩 / 凯瑞-安·莫斯 / 雨果·维文 / 莫妮卡·贝鲁奇 ...</td>\n",
       "      <td>动作 / 科幻</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>138.0</td>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>泰坦尼克号</td>\n",
       "      <td>1997</td>\n",
       "      <td>9.4</td>\n",
       "      <td>1706127.0</td>\n",
       "      <td>詹姆斯·卡梅隆</td>\n",
       "      <td>詹姆斯·卡梅隆</td>\n",
       "      <td>莱昂纳多·迪卡普里奥 / 凯特·温丝莱特 / 比利·赞恩 / 凯西·贝茨 / 弗兰西丝·费舍...</td>\n",
       "      <td>剧情 / 爱情 / 灾难</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>194.0</td>\n",
       "      <td>44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>阿甘正传</td>\n",
       "      <td>1994</td>\n",
       "      <td>9.5</td>\n",
       "      <td>1743966.0</td>\n",
       "      <td>罗伯特·泽米吉斯</td>\n",
       "      <td>艾瑞克·罗斯 / 温斯顿·格鲁姆</td>\n",
       "      <td>汤姆·汉克斯 / 罗宾·怀特 / 加里·西尼斯 / 麦凯尔泰·威廉逊 / 莎莉·菲尔德 / ...</td>\n",
       "      <td>剧情 / 爱情</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>142.0</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220</th>\n",
       "      <td>终结者2：审判日</td>\n",
       "      <td>1991</td>\n",
       "      <td>8.7</td>\n",
       "      <td>282749.0</td>\n",
       "      <td>詹姆斯·卡梅隆</td>\n",
       "      <td>詹姆斯·卡梅隆 / 小威廉·威谢尔</td>\n",
       "      <td>阿诺·施瓦辛格 / 琳达·汉密尔顿 / 爱德华·福隆 / 罗伯特·帕特里克 / 阿尔·伯恩 ...</td>\n",
       "      <td>动作 / 科幻</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>137.0</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>指环王1：魔戒再现</td>\n",
       "      <td>2001</td>\n",
       "      <td>9.0</td>\n",
       "      <td>628224.0</td>\n",
       "      <td>彼得·杰克逊</td>\n",
       "      <td>弗兰·威尔士 / 菲利帕·鲍恩斯 / 彼得·杰克逊 / J·R·R·托尔金</td>\n",
       "      <td>伊利亚·伍德 / 西恩·奥斯汀 / 伊恩·麦克莱恩 / 奥兰多·布鲁姆 / 维果·莫腾森 /...</td>\n",
       "      <td>剧情 / 动作 / 奇幻 / 冒险</td>\n",
       "      <td>新西兰</td>\n",
       "      <td>英语</td>\n",
       "      <td>178.0</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>243</th>\n",
       "      <td>东京教父</td>\n",
       "      <td>2003</td>\n",
       "      <td>9.0</td>\n",
       "      <td>143507.0</td>\n",
       "      <td>今敏</td>\n",
       "      <td>今敏 / 信本敬子</td>\n",
       "      <td>江守彻 / 梅垣义明 / 冈本绫 / 饭塚昭三 / 加藤精三 / 石丸博也 / 槐柳二 / ...</td>\n",
       "      <td>剧情 / 喜剧 / 动画</td>\n",
       "      <td>日本</td>\n",
       "      <td>日语</td>\n",
       "      <td>92.0</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>摩登时代</td>\n",
       "      <td>1936</td>\n",
       "      <td>9.3</td>\n",
       "      <td>231936.0</td>\n",
       "      <td>查理·卓别林</td>\n",
       "      <td>查理·卓别林</td>\n",
       "      <td>查理·卓别林 / 宝莲·高黛 / 亨利·伯格曼 / 蒂尼·桑福德 / 切斯特·康克林 / 汉...</td>\n",
       "      <td>剧情 / 喜剧 / 爱情</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>87.0</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>无敌破坏王</td>\n",
       "      <td>2012</td>\n",
       "      <td>8.7</td>\n",
       "      <td>429804.0</td>\n",
       "      <td>瑞奇·摩尔</td>\n",
       "      <td>菲尔·约翰斯顿 / 珍妮弗·李 / 瑞奇·摩尔 / 吉姆·里尔顿 / 约翰·C·赖利 / 山...</td>\n",
       "      <td>约翰·C·赖利 / 萨拉·西尔弗曼 / 杰克·麦克布瑞尔 / 简·林奇 / 艾伦·图代克 /...</td>\n",
       "      <td>喜剧 / 动画 / 奇幻 / 冒险</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>101.0</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152</th>\n",
       "      <td>时空恋旅人</td>\n",
       "      <td>2013</td>\n",
       "      <td>8.8</td>\n",
       "      <td>469866.0</td>\n",
       "      <td>理查德·柯蒂斯</td>\n",
       "      <td>理查德·柯蒂斯</td>\n",
       "      <td>多姆纳尔·格里森 / 瑞秋·麦克亚当斯 / 比尔·奈伊 / 莉迪亚·威尔逊 / 琳赛·邓肯 ...</td>\n",
       "      <td>喜剧 / 爱情 / 奇幻</td>\n",
       "      <td>英国</td>\n",
       "      <td>英语</td>\n",
       "      <td>123.0</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>黑客帝国3：矩阵革命</td>\n",
       "      <td>2003</td>\n",
       "      <td>8.8</td>\n",
       "      <td>345647.0</td>\n",
       "      <td>莉莉·沃卓斯基 / 拉娜·沃卓斯基</td>\n",
       "      <td>莉莉·沃卓斯基 / 拉娜·沃卓斯基</td>\n",
       "      <td>基努·里维斯 / 劳伦斯·菲什伯恩 / 凯瑞-安·莫斯 / 雨果·维文 / 贾达·萍克·史密...</td>\n",
       "      <td>动作 / 科幻</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>129.0</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             片名  上映年份   评分       评价人数                 导演  \\\n",
       "199   哈利·波特与火焰杯  2005  8.6   449226.0             迈克·内威尔   \n",
       "33    指环王3：王者无敌  2003  9.2   612850.0             彼得·杰克逊   \n",
       "52          教父2  1974  9.2   424440.0        弗朗西斯·福特·科波拉   \n",
       "224        魂断蓝桥  1940  8.8   225318.0             茂文·勒鲁瓦   \n",
       "208         雨中曲  1952  9.0   167372.0     斯坦利·多南 / 吉恩·凯利   \n",
       "141       幸福终点站  2004  8.8   440640.0          史蒂文·斯皮尔伯格   \n",
       "54    指环王2：双塔奇兵  2002  9.1   560238.0             彼得·杰克逊   \n",
       "70       拯救大兵瑞恩  1998  9.0   520707.0          史蒂文·斯皮尔伯格   \n",
       "160         七武士  1954  9.3   153914.0                黑泽明   \n",
       "61         美丽心灵  2001  9.0   611950.0              朗·霍华德   \n",
       "249  黑客帝国2：重装上阵  2003  8.6   305302.0  莉莉·沃卓斯基 / 拉娜·沃卓斯基   \n",
       "4         泰坦尼克号  1997  9.4  1706127.0            詹姆斯·卡梅隆   \n",
       "2          阿甘正传  1994  9.5  1743966.0           罗伯特·泽米吉斯   \n",
       "220    终结者2：审判日  1991  8.7   282749.0            詹姆斯·卡梅隆   \n",
       "57    指环王1：魔戒再现  2001  9.0   628224.0             彼得·杰克逊   \n",
       "243        东京教父  2003  9.0   143507.0                 今敏   \n",
       "87         摩登时代  1936  9.3   231936.0             查理·卓别林   \n",
       "195       无敌破坏王  2012  8.7   429804.0              瑞奇·摩尔   \n",
       "152       时空恋旅人  2013  8.8   469866.0            理查德·柯蒂斯   \n",
       "178  黑客帝国3：矩阵革命  2003  8.8   345647.0  莉莉·沃卓斯基 / 拉娜·沃卓斯基   \n",
       "\n",
       "                                                    编剧  \\\n",
       "199                                  史蒂夫·克洛夫斯 / J·K·罗琳   \n",
       "33               弗兰·威尔士 / 菲利帕·鲍恩斯 / 彼得·杰克逊 / J·R·R·托尔金   \n",
       "52                                弗朗西斯·福特·科波拉 / 马里奥·普佐   \n",
       "224           塞缪尔·N·贝尔曼 / 汉斯·拉莫 / 乔治·弗罗斯切尔 / 罗伯特·E·舍伍德   \n",
       "208                                     贝蒂·康登 / 阿多夫·格林   \n",
       "141                         安德鲁·尼科尔 / 萨沙·杰瓦西  / 杰夫·内桑森   \n",
       "54     弗兰·威尔士 / 菲利帕·鲍恩斯 / 斯蒂芬·辛克莱 / 彼得·杰克逊 / J·R·R·托尔金   \n",
       "70                                             罗伯特·罗达特   \n",
       "160                                   黑泽明 / 桥本忍 / 小国英雄   \n",
       "61                                  阿齐瓦·高斯曼 / 西尔维娅·纳萨尔   \n",
       "249                                  莉莉·沃卓斯基 / 拉娜·沃卓斯基   \n",
       "4                                              詹姆斯·卡梅隆   \n",
       "2                                     艾瑞克·罗斯 / 温斯顿·格鲁姆   \n",
       "220                                  詹姆斯·卡梅隆 / 小威廉·威谢尔   \n",
       "57               弗兰·威尔士 / 菲利帕·鲍恩斯 / 彼得·杰克逊 / J·R·R·托尔金   \n",
       "243                                          今敏 / 信本敬子   \n",
       "87                                              查理·卓别林   \n",
       "195  菲尔·约翰斯顿 / 珍妮弗·李 / 瑞奇·摩尔 / 吉姆·里尔顿 / 约翰·C·赖利 / 山...   \n",
       "152                                            理查德·柯蒂斯   \n",
       "178                                  莉莉·沃卓斯基 / 拉娜·沃卓斯基   \n",
       "\n",
       "                                                    主演                 类型  \\\n",
       "199  丹尼尔·雷德克里夫 / 艾玛·沃森 / 鲁伯特·格林特 / 迈克尔·刚本 / 玛吉·史密斯 ...       悬疑 / 奇幻 / 冒险   \n",
       "33   伊利亚·伍德 / 西恩·奥斯汀 / 维果·莫腾森 / 奥兰多·布鲁姆 / 伊恩·麦克莱恩 /...  剧情 / 动作 / 奇幻 / 冒险   \n",
       "52   阿尔·帕西诺 / 罗伯特·杜瓦尔 / 黛安·基顿 / 罗伯特·德尼罗 / 约翰·凯泽尔 / ...            剧情 / 犯罪   \n",
       "224  费雯·丽 / 罗伯特·泰勒 / 露塞尔·沃特森 / 弗吉尼亚·菲尔德 / 玛丽亚·彭斯卡娅 ...       剧情 / 爱情 / 战争   \n",
       "208  吉恩·凯利 / 唐纳德·奥康纳 / 黛比·雷诺斯 / 简·哈根 / 米勒德·米切尔 / 赛德...       喜剧 / 爱情 / 歌舞   \n",
       "141  汤姆·汉克斯 / 凯瑟琳·泽塔-琼斯 / 斯坦利·图齐 / 齐·麦克布赖德 / 迭戈·卢纳 ...       剧情 / 喜剧 / 爱情   \n",
       "54   伊利亚·伍德 / 西恩·奥斯汀 / 多米尼克·莫纳汉 / 奥兰多·布鲁姆 / 维果·莫腾森 ...  剧情 / 动作 / 奇幻 / 冒险   \n",
       "70   汤姆·汉克斯 / 汤姆·塞兹摩尔 / 爱德华·伯恩斯 / 巴里·佩珀 / 亚当·戈德堡 / ...            剧情 / 战争   \n",
       "160  三船敏郎 / 志村乔 / 津岛惠子 / 岛崎雪子 / 藤原釜足 / 加东大介 / 木村功 /...       剧情 / 动作 / 冒险   \n",
       "61   罗素·克劳 / 艾德·哈里斯 / 詹妮弗·康纳利 / 克里斯托弗·普卢默 / 保罗·贝坦尼 ...            剧情 / 传记   \n",
       "249  基努·里维斯 / 劳伦斯·菲什伯恩 / 凯瑞-安·莫斯 / 雨果·维文 / 莫妮卡·贝鲁奇 ...            动作 / 科幻   \n",
       "4    莱昂纳多·迪卡普里奥 / 凯特·温丝莱特 / 比利·赞恩 / 凯西·贝茨 / 弗兰西丝·费舍...       剧情 / 爱情 / 灾难   \n",
       "2    汤姆·汉克斯 / 罗宾·怀特 / 加里·西尼斯 / 麦凯尔泰·威廉逊 / 莎莉·菲尔德 / ...            剧情 / 爱情   \n",
       "220  阿诺·施瓦辛格 / 琳达·汉密尔顿 / 爱德华·福隆 / 罗伯特·帕特里克 / 阿尔·伯恩 ...            动作 / 科幻   \n",
       "57   伊利亚·伍德 / 西恩·奥斯汀 / 伊恩·麦克莱恩 / 奥兰多·布鲁姆 / 维果·莫腾森 /...  剧情 / 动作 / 奇幻 / 冒险   \n",
       "243  江守彻 / 梅垣义明 / 冈本绫 / 饭塚昭三 / 加藤精三 / 石丸博也 / 槐柳二 / ...       剧情 / 喜剧 / 动画   \n",
       "87   查理·卓别林 / 宝莲·高黛 / 亨利·伯格曼 / 蒂尼·桑福德 / 切斯特·康克林 / 汉...       剧情 / 喜剧 / 爱情   \n",
       "195  约翰·C·赖利 / 萨拉·西尔弗曼 / 杰克·麦克布瑞尔 / 简·林奇 / 艾伦·图代克 /...  喜剧 / 动画 / 奇幻 / 冒险   \n",
       "152  多姆纳尔·格里森 / 瑞秋·麦克亚当斯 / 比尔·奈伊 / 莉迪亚·威尔逊 / 琳赛·邓肯 ...       喜剧 / 爱情 / 奇幻   \n",
       "178  基努·里维斯 / 劳伦斯·菲什伯恩 / 凯瑞-安·莫斯 / 雨果·维文 / 贾达·萍克·史密...            动作 / 科幻   \n",
       "\n",
       "    国家/地区   语言  时长(分钟)  主演人数  \n",
       "199    英国  英语    157.0    67  \n",
       "33     美国  英语    201.0    63  \n",
       "52     美国  英语    202.0    62  \n",
       "224    美国  英语    108.0    59  \n",
       "208    美国   英语   103.0    53  \n",
       "141    美国  英语    128.0    51  \n",
       "54     美国  英语    179.0    51  \n",
       "70     美国  英语    169.0    48  \n",
       "160    日本   日语   207.0    47  \n",
       "61     美国   英语   135.0    46  \n",
       "249    美国  英语    138.0    46  \n",
       "4      美国  英语    194.0    44  \n",
       "2      美国   英语   142.0    41  \n",
       "220    美国  英语    137.0    39  \n",
       "57   新西兰   英语    178.0    38  \n",
       "243    日本  日语     92.0    37  \n",
       "87     美国   英语    87.0    37  \n",
       "195    美国   英语   101.0    37  \n",
       "152    英国   英语   123.0    37  \n",
       "178    美国  英语    129.0    34  "
      ]
     },
     "execution_count": 147,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['主演人数'] = df.主演.map(lambda x: np.size(np.unique(x.split('/'))))\n",
    "\n",
    "df.sort_values('主演人数', ascending=False)[:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>movie</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>actor</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>张国荣</th>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>梁朝伟</th>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>艾伦·瑞克曼</th>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>张曼玉</th>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>雨果·维文</th>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>汤姆·汉克斯</th>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>加里·奥德曼</th>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>莱昂纳多·迪卡普里奥</th>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>伊桑·霍克</th>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>马特·达蒙</th>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>周星驰</th>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>拉尔夫·费因斯</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>鲁伯特·格林特</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>布拉德·皮特</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>琼·艾伦</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>丹尼尔·雷德克里夫</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>约翰·拉岑贝格</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>迈克尔·凯恩</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>艾玛·沃森</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>汤姆·费尔顿</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            movie\n",
       "actor            \n",
       "张国荣             8\n",
       "梁朝伟             8\n",
       "艾伦·瑞克曼          7\n",
       "张曼玉             7\n",
       "雨果·维文           7\n",
       "汤姆·汉克斯          6\n",
       "加里·奥德曼          6\n",
       "莱昂纳多·迪卡普里奥      6\n",
       "伊桑·霍克           6\n",
       "马特·达蒙           6\n",
       "周星驰             6\n",
       "拉尔夫·费因斯         5\n",
       "鲁伯特·格林特         5\n",
       "布拉德·皮特          5\n",
       "琼·艾伦            5\n",
       "丹尼尔·雷德克里夫       5\n",
       "约翰·拉岑贝格         5\n",
       "迈克尔·凯恩          5\n",
       "艾玛·沃森           5\n",
       "汤姆·费尔顿          5"
      ]
     },
     "execution_count": 159,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.pivot_table(index='actor', values='movie', aggfunc=np.size).sort_values('movie', ascending=False)[:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 241,
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "temp = df.groupby('国家/地区').size().sort_values(ascending=False)\n",
    "ax = temp.plot.bar(figsize=(16,8), width=0.8, alpha=0.7, title='years area movies')\n",
    "\n",
    "for x, y in zip(range(temp.size), temp):\n",
    "    ax.text(x-0.1, y + 2, str(y), fontsize=12, color='b')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>评分</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>国家/地区</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8.850000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>中国</th>\n",
       "      <td>8.847500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>丹麦</th>\n",
       "      <td>9.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>伊朗</th>\n",
       "      <td>9.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>印度</th>\n",
       "      <td>8.875000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>巴西</th>\n",
       "      <td>9.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>德国</th>\n",
       "      <td>8.875000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>意大利</th>\n",
       "      <td>9.050000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>新西兰</th>\n",
       "      <td>9.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>日本</th>\n",
       "      <td>8.653125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>法国</th>\n",
       "      <td>9.028571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>泰国</th>\n",
       "      <td>8.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>澳大利亚</th>\n",
       "      <td>8.733333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>爱尔兰</th>\n",
       "      <td>8.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>瑞典</th>\n",
       "      <td>8.900000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>美国</th>\n",
       "      <td>8.674312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>英国</th>\n",
       "      <td>8.823529</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>西班牙</th>\n",
       "      <td>8.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>阿根廷</th>\n",
       "      <td>8.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>韩国</th>\n",
       "      <td>8.945455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>黎巴嫩</th>\n",
       "      <td>9.100000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             评分\n",
       "国家/地区          \n",
       "0      8.850000\n",
       "中国     8.847500\n",
       "丹麦     9.100000\n",
       "伊朗     9.200000\n",
       "印度     8.875000\n",
       "巴西     9.000000\n",
       "德国     8.875000\n",
       "意大利    9.050000\n",
       "新西兰    9.000000\n",
       "日本     8.653125\n",
       "法国     9.028571\n",
       "泰国     8.400000\n",
       "澳大利亚   8.733333\n",
       "爱尔兰    8.800000\n",
       "瑞典     8.900000\n",
       "美国     8.674312\n",
       "英国     8.823529\n",
       "西班牙    8.800000\n",
       "阿根廷    8.800000\n",
       "韩国     8.945455\n",
       "黎巴嫩    9.100000"
      ]
     },
     "execution_count": 189,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.fillna(0, inplace=True)\n",
    "\n",
    "df.pivot_table(index='国家/地区', values='评分',aggfunc='mean')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 240,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1440x540 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rcParams[\"figure.dpi\"] = 90\n",
    "\n",
    "dd = {}\n",
    "for k, v in df.iterrows():\n",
    "    ds = [x.strip() for x in v.导演.split('/')]\n",
    "    for d in ds:\n",
    "        if d in dd:\n",
    "            dd[d] += 1\n",
    "        else:\n",
    "            dd[d] = 1\n",
    "\n",
    "temp = pd.DataFrame({'dirictor': dd.keys(), 'num': dd.values()})\n",
    "ptemp = temp.sort_values('num', ascending=False)[:20]\n",
    "\n",
    "ax = ptemp.plot.bar(figsize=(16,6),width=0.8, alpha= 0.8,color='skyblue')\n",
    "ax.set_xticklabels(ptemp.dirictor, fontsize=10)\n",
    "ax.legend(['电影数量'], fontsize=16)\n",
    "\n",
    "for x, y in zip(range(ptemp.size), ptemp.num):\n",
    "    ax.text(x, y+0.1, str(y))\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>dirictor</th>\n",
       "      <th>num</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>宫崎骏</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>克里斯托弗·诺兰</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>史蒂文·斯皮尔伯格</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>李安</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>王家卫</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>大卫·芬奇</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>是枝裕和</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>今敏</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>彼得·杰克逊</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>姜文</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>莉莉·沃卓斯基</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>拉娜·沃卓斯基</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>昆汀·塔伦蒂诺</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>李·昂克里奇</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>弗朗西斯·福特·科波拉</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>理查德·林克莱特</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>彼特·道格特</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>刘镇伟</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>詹姆斯·卡梅隆</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>朱塞佩·托纳多雷</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        dirictor  num\n",
       "6            宫崎骏    8\n",
       "8       克里斯托弗·诺兰    7\n",
       "7      史蒂文·斯皮尔伯格    6\n",
       "42            李安    5\n",
       "77           王家卫    5\n",
       "52         大卫·芬奇    4\n",
       "95          是枝裕和    4\n",
       "100           今敏    3\n",
       "37        彼得·杰克逊    3\n",
       "44            姜文    3\n",
       "55       莉莉·沃卓斯基    3\n",
       "56       拉娜·沃卓斯基    3\n",
       "72       昆汀·塔伦蒂诺    3\n",
       "29        李·昂克里奇    3\n",
       "22   弗朗西斯·福特·科波拉    3\n",
       "104     理查德·林克莱特    3\n",
       "39        彼特·道格特    3\n",
       "15           刘镇伟    3\n",
       "4        詹姆斯·卡梅隆    3\n",
       "11      朱塞佩·托纳多雷    3"
      ]
     },
     "execution_count": 208,
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   "source": [
    "ptemp\n"
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    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>片名</th>\n",
       "      <th>上映年份</th>\n",
       "      <th>评分</th>\n",
       "      <th>评价人数</th>\n",
       "      <th>导演</th>\n",
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       "      <th>主演人数</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>肖申克的救赎</td>\n",
       "      <td>1994</td>\n",
       "      <td>9.7</td>\n",
       "      <td>2317937.0</td>\n",
       "      <td>弗兰克·德拉邦特</td>\n",
       "      <td>弗兰克·德拉邦特 / 斯蒂芬·金</td>\n",
       "      <td>蒂姆·罗宾斯 / 摩根·弗里曼 / 鲍勃·冈顿 / 威廉姆·赛德勒 / 克兰西·布朗 / 吉...</td>\n",
       "      <td>剧情 / 犯罪</td>\n",
       "      <td>美国</td>\n",
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       "      <td>142.0</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>霸王别姬</td>\n",
       "      <td>1993</td>\n",
       "      <td>9.6</td>\n",
       "      <td>1720638.0</td>\n",
       "      <td>陈凯歌</td>\n",
       "      <td>芦苇 / 李碧华</td>\n",
       "      <td>张国荣 / 张丰毅 / 巩俐 / 葛优 / 英达 / 蒋雯丽 / 吴大维 / 吕齐 / 雷汉...</td>\n",
       "      <td>剧情 / 爱情 / 同性</td>\n",
       "      <td>中国</td>\n",
       "      <td>汉语普通话</td>\n",
       "      <td>171.0</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>阿甘正传</td>\n",
       "      <td>1994</td>\n",
       "      <td>9.5</td>\n",
       "      <td>1743966.0</td>\n",
       "      <td>罗伯特·泽米吉斯</td>\n",
       "      <td>艾瑞克·罗斯 / 温斯顿·格鲁姆</td>\n",
       "      <td>汤姆·汉克斯 / 罗宾·怀特 / 加里·西尼斯 / 麦凯尔泰·威廉逊 / 莎莉·菲尔德 / ...</td>\n",
       "      <td>剧情 / 爱情</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>142.0</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>这个杀手不太冷</td>\n",
       "      <td>1994</td>\n",
       "      <td>9.4</td>\n",
       "      <td>1922740.0</td>\n",
       "      <td>吕克·贝松</td>\n",
       "      <td>吕克·贝松</td>\n",
       "      <td>让·雷诺 / 娜塔莉·波特曼 / 加里·奥德曼 / 丹尼·爱罗 / 彼得·阿佩尔 / 迈克尔...</td>\n",
       "      <td>剧情 / 动作 / 犯罪</td>\n",
       "      <td>法国</td>\n",
       "      <td>英语</td>\n",
       "      <td>110.0</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>泰坦尼克号</td>\n",
       "      <td>1997</td>\n",
       "      <td>9.4</td>\n",
       "      <td>1706127.0</td>\n",
       "      <td>詹姆斯·卡梅隆</td>\n",
       "      <td>詹姆斯·卡梅隆</td>\n",
       "      <td>莱昂纳多·迪卡普里奥 / 凯特·温丝莱特 / 比利·赞恩 / 凯西·贝茨 / 弗兰西丝·费舍...</td>\n",
       "      <td>剧情 / 爱情 / 灾难</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>194.0</td>\n",
       "      <td>44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>257</th>\n",
       "      <td>浪潮</td>\n",
       "      <td>2008</td>\n",
       "      <td>8.7</td>\n",
       "      <td>223511.0</td>\n",
       "      <td>丹尼斯·甘塞尔</td>\n",
       "      <td>丹尼斯·甘塞尔 / 彼得·图万斯 / 约翰尼·道金斯 / 罗恩·比恩巴赫 / 罗恩·琼斯</td>\n",
       "      <td>于尔根·福格尔 / 弗雷德里克·劳 / 马克思·雷迈特 / 詹妮弗·乌尔里希 / 克里斯蒂安...</td>\n",
       "      <td>剧情 / 惊悚</td>\n",
       "      <td>0</td>\n",
       "      <td>德语</td>\n",
       "      <td>107.0</td>\n",
       "      <td>10</td>\n",
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       "    <tr>\n",
       "      <th>258</th>\n",
       "      <td>小萝莉的猴神大叔</td>\n",
       "      <td>2015</td>\n",
       "      <td>8.4</td>\n",
       "      <td>404886.0</td>\n",
       "      <td>卡比尔·汗</td>\n",
       "      <td>卡比尔·汗 / 维杰耶德拉·普拉萨德</td>\n",
       "      <td>萨尔曼·汗 / 哈莎莉·马洛特拉 / 卡琳娜·卡普尔 / 纳瓦祖丁·席迪圭 / 欧姆·普瑞 ...</td>\n",
       "      <td>剧情 / 喜剧 / 动作</td>\n",
       "      <td>印度</td>\n",
       "      <td>印地语</td>\n",
       "      <td>159.0</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>259</th>\n",
       "      <td>追随</td>\n",
       "      <td>1998</td>\n",
       "      <td>8.9</td>\n",
       "      <td>149521.0</td>\n",
       "      <td>克里斯托弗·诺兰</td>\n",
       "      <td>克里斯托弗·诺兰</td>\n",
       "      <td>杰里米·西奥伯德 / 亚历克斯·霍 / 露西·拉塞尔 / 约翰·诺兰 / 迪克·布拉德塞尔 ...</td>\n",
       "      <td>悬疑 / 惊悚 / 犯罪</td>\n",
       "      <td>英国</td>\n",
       "      <td>英语</td>\n",
       "      <td>69.0</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260</th>\n",
       "      <td>网络谜踪</td>\n",
       "      <td>2018</td>\n",
       "      <td>8.6</td>\n",
       "      <td>430811.0</td>\n",
       "      <td>阿尼什·查甘蒂</td>\n",
       "      <td>阿尼什·查甘蒂 / 赛弗·奥哈尼安</td>\n",
       "      <td>约翰·赵 / 米切尔·拉 / 黛博拉·梅辛 / 约瑟夫·李 / 萨拉·米博·孙 / 亚历克丝...</td>\n",
       "      <td>剧情 / 悬疑 / 惊悚 / 犯罪</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>102.0</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261</th>\n",
       "      <td>黑鹰坠落</td>\n",
       "      <td>2001</td>\n",
       "      <td>8.7</td>\n",
       "      <td>239402.0</td>\n",
       "      <td>雷德利·斯科特</td>\n",
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       "      <td>动作 / 历史 / 战争</td>\n",
       "      <td>美国</td>\n",
       "      <td>英语</td>\n",
       "      <td>144.0</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>249 rows × 12 columns</p>\n",
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      "text/plain": [
       "           片名  上映年份   评分       评价人数        导演  \\\n",
       "0      肖申克的救赎  1994  9.7  2317937.0  弗兰克·德拉邦特   \n",
       "1        霸王别姬  1993  9.6  1720638.0       陈凯歌   \n",
       "2        阿甘正传  1994  9.5  1743966.0  罗伯特·泽米吉斯   \n",
       "3     这个杀手不太冷  1994  9.4  1922740.0     吕克·贝松   \n",
       "4       泰坦尼克号  1997  9.4  1706127.0   詹姆斯·卡梅隆   \n",
       "..        ...   ...  ...        ...       ...   \n",
       "257        浪潮  2008  8.7   223511.0   丹尼斯·甘塞尔   \n",
       "258  小萝莉的猴神大叔  2015  8.4   404886.0     卡比尔·汗   \n",
       "259        追随  1998  8.9   149521.0  克里斯托弗·诺兰   \n",
       "260      网络谜踪  2018  8.6   430811.0   阿尼什·查甘蒂   \n",
       "261      黑鹰坠落  2001  8.7   239402.0   雷德利·斯科特   \n",
       "\n",
       "                                               编剧  \\\n",
       "0                                弗兰克·德拉邦特 / 斯蒂芬·金   \n",
       "1                                        芦苇 / 李碧华   \n",
       "2                                艾瑞克·罗斯 / 温斯顿·格鲁姆   \n",
       "3                                           吕克·贝松   \n",
       "4                                         詹姆斯·卡梅隆   \n",
       "..                                            ...   \n",
       "257  丹尼斯·甘塞尔 / 彼得·图万斯 / 约翰尼·道金斯 / 罗恩·比恩巴赫 / 罗恩·琼斯   \n",
       "258                            卡比尔·汗 / 维杰耶德拉·普拉萨德   \n",
       "259                                      克里斯托弗·诺兰   \n",
       "260                             阿尼什·查甘蒂 / 赛弗·奥哈尼安   \n",
       "261                                  肯·诺兰 / 马克·鲍登   \n",
       "\n",
       "                                                    主演                 类型  \\\n",
       "0    蒂姆·罗宾斯 / 摩根·弗里曼 / 鲍勃·冈顿 / 威廉姆·赛德勒 / 克兰西·布朗 / 吉...            剧情 / 犯罪   \n",
       "1    张国荣 / 张丰毅 / 巩俐 / 葛优 / 英达 / 蒋雯丽 / 吴大维 / 吕齐 / 雷汉...       剧情 / 爱情 / 同性   \n",
       "2    汤姆·汉克斯 / 罗宾·怀特 / 加里·西尼斯 / 麦凯尔泰·威廉逊 / 莎莉·菲尔德 / ...            剧情 / 爱情   \n",
       "3    让·雷诺 / 娜塔莉·波特曼 / 加里·奥德曼 / 丹尼·爱罗 / 彼得·阿佩尔 / 迈克尔...       剧情 / 动作 / 犯罪   \n",
       "4    莱昂纳多·迪卡普里奥 / 凯特·温丝莱特 / 比利·赞恩 / 凯西·贝茨 / 弗兰西丝·费舍...       剧情 / 爱情 / 灾难   \n",
       "..                                                 ...                ...   \n",
       "257  于尔根·福格尔 / 弗雷德里克·劳 / 马克思·雷迈特 / 詹妮弗·乌尔里希 / 克里斯蒂安...            剧情 / 惊悚   \n",
       "258  萨尔曼·汗 / 哈莎莉·马洛特拉 / 卡琳娜·卡普尔 / 纳瓦祖丁·席迪圭 / 欧姆·普瑞 ...       剧情 / 喜剧 / 动作   \n",
       "259  杰里米·西奥伯德 / 亚历克斯·霍 / 露西·拉塞尔 / 约翰·诺兰 / 迪克·布拉德塞尔 ...       悬疑 / 惊悚 / 犯罪   \n",
       "260  约翰·赵 / 米切尔·拉 / 黛博拉·梅辛 / 约瑟夫·李 / 萨拉·米博·孙 / 亚历克丝...  剧情 / 悬疑 / 惊悚 / 犯罪   \n",
       "261  乔什·哈奈特 / 伊万·麦克格雷格 / 汤姆·塞兹摩尔 / 金·寇兹 / 艾文·布莱纳 / ...       动作 / 历史 / 战争   \n",
       "\n",
       "    国家/地区     语言  时长(分钟)  主演人数  \n",
       "0      美国     英语   142.0    25  \n",
       "1      中国  汉语普通话   171.0    20  \n",
       "2      美国     英语   142.0    41  \n",
       "3      法国    英语    110.0    16  \n",
       "4      美国    英语    194.0    44  \n",
       "..    ...    ...     ...   ...  \n",
       "257     0     德语   107.0    10  \n",
       "258    印度   印地语    159.0    12  \n",
       "259    英国     英语    69.0    19  \n",
       "260    美国     英语   102.0    24  \n",
       "261    美国    英语    144.0    11  \n",
       "\n",
       "[249 rows x 12 columns]"
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